Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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//===-- PPCScheduleP7.td - PPC P7 Scheduling Definitions ---*- tablegen -*-===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This file defines the itinerary class data for the POWER7 processor.
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//
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//===----------------------------------------------------------------------===//
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// Primary reference:
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// IBM POWER7 multicore server processor
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// B. Sinharoy, et al.
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// IBM J. Res. & Dev. (55) 3. May/June 2011.
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// Scheduling for the P7 involves tracking two types of resources:
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// 1. The dispatch bundle slots
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// 2. The functional unit resources
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// Dispatch units:
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def P7_DU1 : FuncUnit;
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def P7_DU2 : FuncUnit;
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def P7_DU3 : FuncUnit;
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def P7_DU4 : FuncUnit;
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def P7_DU5 : FuncUnit;
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def P7_DU6 : FuncUnit;
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def P7_LS1 : FuncUnit; // Load/Store pipeline 1
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def P7_LS2 : FuncUnit; // Load/Store pipeline 2
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def P7_FX1 : FuncUnit; // FX pipeline 1
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def P7_FX2 : FuncUnit; // FX pipeline 2
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// VS pipeline 1 (vector integer ops. always here)
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def P7_VS1 : FuncUnit; // VS pipeline 1
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// VS pipeline 2 (128-bit stores and perms. here)
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def P7_VS2 : FuncUnit; // VS pipeline 2
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def P7_CRU : FuncUnit; // CR unit (CR logicals and move-from-SPRs)
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def P7_BRU : FuncUnit; // BR unit
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// Notes:
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// Each LSU pipeline can also execute FX add and logical instructions.
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// Each LSU pipeline can complete a load or store in one cycle.
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//
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// Each store is broken into two parts, AGEN goes to the LSU while a
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// "data steering" op. goes to the FXU or VSU.
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//
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// FX loads have a two cycle load-to-use latency (so one "bubble" cycle).
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// VSU loads have a three cycle load-to-use latency (so two "bubble" cycle).
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//
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// Frequent FX ops. take only one cycle and results can be used again in the
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// next cycle (there is a self-bypass). Getting results from the other FX
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// pipeline takes an additional cycle.
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//
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// The VSU XS is similar to the POWER6, but with a pipeline length of 2 cycles
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// (instead of 3 cycles on the POWER6). VSU XS handles vector FX-style ops.
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// Dispatch of an instruction to VS1 that uses four single prec. inputs
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// (either to a float or XC op). prevents dispatch in that cycle to VS2 of any
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// floating point instruction.
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//
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// The VSU PM is similar to the POWER6, but with a pipeline length of 3 cycles
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// (instead of 4 cycles on the POWER6). vsel is handled by the PM pipeline
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// (unlike on the POWER6).
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//
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// FMA from the VSUs can forward results in 6 cycles. VS1 XS and vector FP
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// share the same write-back, and have a 5-cycle latency difference, so the
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// IFU/IDU will not dispatch an XS instructon 5 cycles after a vector FP
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// op. has been dispatched to VS1.
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//
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// Three cycles after an L1 cache hit, a dependent VSU instruction can issue.
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//
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// Instruction dispatch groups have (at most) four non-branch instructions, and
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// two branches. Unlike on the POWER4/5, a branch does not automatically
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// end the dispatch group, but a second branch must be the last in the group.
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def P7Itineraries : ProcessorItineraries<
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[P7_DU1, P7_DU2, P7_DU3, P7_DU4, P7_DU5, P7_DU6,
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P7_LS1, P7_LS2, P7_FX1, P7_FX2, P7_VS1, P7_VS2, P7_CRU, P7_BRU], [], [
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InstrItinData<IIC_IntSimple , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2,
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P7_LS1, P7_LS2]>],
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[1, 1, 1]>,
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InstrItinData<IIC_IntGeneral , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1, 1]>,
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2015-02-02 01:52:16 +08:00
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InstrItinData<IIC_IntISEL, [InstrStage<1, [P7_DU1], 0>,
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InstrStage<1, [P7_FX1, P7_FX2], 0>,
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InstrStage<1, [P7_BRU]>],
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[1, 1, 1, 1]>,
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Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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InstrItinData<IIC_IntCompare , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1, 1]>,
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2013-12-12 08:19:11 +08:00
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// FIXME: Add record-form itinerary data.
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Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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InstrItinData<IIC_IntDivW , [InstrStage<1, [P7_DU1], 0>,
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InstrStage<1, [P7_DU2], 0>,
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InstrStage<36, [P7_FX1, P7_FX2]>],
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[36, 1, 1]>,
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InstrItinData<IIC_IntDivD , [InstrStage<1, [P7_DU1], 0>,
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InstrStage<1, [P7_DU2], 0>,
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InstrStage<68, [P7_FX1, P7_FX2]>],
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[68, 1, 1]>,
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InstrItinData<IIC_IntMulHW , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[4, 1, 1]>,
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InstrItinData<IIC_IntMulHWU , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[4, 1, 1]>,
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InstrItinData<IIC_IntMulLI , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[4, 1, 1]>,
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InstrItinData<IIC_IntRotate , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1, 1]>,
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InstrItinData<IIC_IntRotateD , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1, 1]>,
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InstrItinData<IIC_IntShift , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1, 1]>,
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InstrItinData<IIC_IntTrapW , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1]>,
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InstrItinData<IIC_IntTrapD , [InstrStage<1, [P7_DU1, P7_DU2,
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P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[1, 1]>,
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InstrItinData<IIC_BrB , [InstrStage<1, [P7_DU5, P7_DU6], 0>,
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InstrStage<1, [P7_BRU]>],
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[3, 1, 1]>,
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2014-01-03 05:38:26 +08:00
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InstrItinData<IIC_BrCR , [InstrStage<1, [P7_DU1], 0>,
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InstrStage<1, [P7_CRU]>],
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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[3, 1, 1]>,
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InstrItinData<IIC_BrMCR , [InstrStage<1, [P7_DU5, P7_DU6], 0>,
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InstrStage<1, [P7_BRU]>],
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[3, 1, 1]>,
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InstrItinData<IIC_BrMCRX , [InstrStage<1, [P7_DU5, P7_DU6], 0>,
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InstrStage<1, [P7_BRU]>],
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[3, 1, 1]>,
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InstrItinData<IIC_LdStLoad , [InstrStage<1, [P7_DU1, P7_DU2,
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|
P7_DU3, P7_DU4], 0>,
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InstrStage<1, [P7_LS1, P7_LS2]>],
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[2, 1, 1]>,
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InstrItinData<IIC_LdStLoadUpd , [InstrStage<1, [P7_DU1], 0>,
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InstrStage<1, [P7_DU2], 0>,
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|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
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InstrStage<1, [P7_FX1, P7_FX2]>],
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[2, 2, 1, 1]>,
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|
InstrItinData<IIC_LdStLoadUpdX, [InstrStage<1, [P7_DU1], 0>,
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|
InstrStage<1, [P7_DU2], 0>,
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|
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|
InstrStage<1, [P7_DU3], 0>,
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|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[2, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLDU , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[2, 2, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLDUX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLFD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLVecX , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLFDU , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLFDUX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLHA , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLHAU , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[4, 4, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLHAUX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[4, 4, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLWA , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLWARX, [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLDARX, [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[3, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStLMW , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[2, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStStore , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTDU , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[2, 1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTDUX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[2, 1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTFD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTFDU , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[2, 1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTVEBX , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2], 0>,
|
|
|
|
InstrStage<1, [P7_VS2]>],
|
|
|
|
[1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTDCX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_LdStSTWCX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_LS1, P7_LS2]>],
|
|
|
|
[1, 1, 1]>,
|
2013-12-12 08:19:11 +08:00
|
|
|
InstrItinData<IIC_BrMCRX , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_DU2], 0>,
|
|
|
|
InstrStage<1, [P7_DU3], 0>,
|
|
|
|
InstrStage<1, [P7_DU4], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_CRU]>,
|
|
|
|
InstrStage<1, [P7_FX1, P7_FX2]>],
|
|
|
|
[3, 1]>, // mtcr
|
|
|
|
InstrItinData<IIC_SprMFCR , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_CRU]>],
|
|
|
|
[6, 1]>,
|
|
|
|
InstrItinData<IIC_SprMFCRF , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_CRU]>],
|
|
|
|
[3, 1]>,
|
2013-12-12 08:19:11 +08:00
|
|
|
InstrItinData<IIC_SprMTSPR , [InstrStage<1, [P7_DU1], 0>,
|
|
|
|
InstrStage<1, [P7_FX1]>],
|
|
|
|
[4, 1]>, // mtctr
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrItinData<IIC_FPGeneral , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[5, 1, 1]>,
|
[PowerPC] Fix the PPCInstrInfo::getInstrLatency implementation
PowerPC uses itineraries to describe processor pipelines (and dispatch-group
restrictions for P7/P8 cores). Unfortunately, the target-independent
implementation of TII.getInstrLatency calls ItinData->getStageLatency, and that
looks for the largest cycle count in the pipeline for any given instruction.
This, however, yields the wrong answer for the PPC itineraries, because we
don't encode the full pipeline. Because the functional units are fully
pipelined, we only model the initial stages (there are no relevant hazards in
the later stages to model), and so the technique employed by getStageLatency
does not really work. Instead, we should take the maximum output operand
latency, and that's what PPCInstrInfo::getInstrLatency now does.
This caused some test-case churn, including two unfortunate side effects.
First, the new arrangement of copies we get from function parameters now
sometimes blocks VSX FMA mutation (a FIXME has been added to the code and the
test cases), and we have one significant test-suite regression:
SingleSource/Benchmarks/BenchmarkGame/spectral-norm
56.4185% +/- 18.9398%
In this benchmark we have a loop with a vectorized FP divide, and it with the
new scheduling both divides end up in the same dispatch group (which in this
case seems to cause a problem, although why is not exactly clear). The grouping
structure is hard to predict from the bottom of the loop, and there may not be
much we can do to fix this.
Very few other test-suite performance effects were really significant, but
almost all weakly favor this change. However, in light of the issues
highlighted above, I've left the old behavior available via a
command-line flag.
llvm-svn: 242188
2015-07-15 04:02:02 +08:00
|
|
|
InstrItinData<IIC_FPAddSub , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[5, 1, 1]>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrItinData<IIC_FPCompare , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[8, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPDivD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[33, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPDivS , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[27, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPSqrtD , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[44, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPSqrtS , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[32, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPFused , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[5, 1, 1, 1]>,
|
|
|
|
InstrItinData<IIC_FPRes , [InstrStage<1, [P7_DU1, P7_DU2,
|
|
|
|
P7_DU3, P7_DU4], 0>,
|
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[5, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecGeneral , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1]>],
|
|
|
|
[2, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecVSL , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1]>],
|
|
|
|
[2, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecVSR , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1]>],
|
|
|
|
[2, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecFP , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[6, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecFPCompare, [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[6, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecFPRound , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1, P7_VS2]>],
|
|
|
|
[6, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecComplex , [InstrStage<1, [P7_DU1], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
|
|
|
InstrStage<1, [P7_VS1]>],
|
|
|
|
[7, 1, 1]>,
|
2014-04-01 01:02:10 +08:00
|
|
|
InstrItinData<IIC_VecPerm , [InstrStage<1, [P7_DU1, P7_DU2], 0>,
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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InstrStage<1, [P7_VS2]>],
|
2014-03-29 21:20:31 +08:00
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[3, 1, 1]>
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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]>;
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// ===---------------------------------------------------------------------===//
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// P7 machine model for scheduling and other instruction cost heuristics.
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def P7Model : SchedMachineModel {
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let IssueWidth = 6; // 4 (non-branch) instructions are dispatched per cycle.
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// Note that the dispatch bundle size is 6 (including
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// branches), but the total internal issue bandwidth per
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// cycle (from all queues) is 8.
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let LoadLatency = 3; // Optimistic load latency assuming bypass.
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// This is overriden by OperandCycles if the
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// Itineraries are queried instead.
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let MispredictPenalty = 16;
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2015-01-10 08:31:10 +08:00
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// Try to make sure we have at least 10 dispatch groups in a loop.
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let LoopMicroOpBufferSize = 40;
|
2015-01-09 23:51:16 +08:00
|
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2016-03-02 04:03:21 +08:00
|
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|
let CompleteModel = 0;
|
|
|
|
|
Add a scheduling model (with itinerary) for the PPC POWER7
This adds a scheduling model for the POWER7 (P7) core, and enables the
machine-instruction scheduler when targeting the P7. Scheduling for the P7,
like earlier ooo PPC cores, requires considering both dispatch group hazards,
and functional unit resources and latencies. These are both modeled in a
combined itinerary. Dispatch group formation is still handled by the post-RA
scheduler (which still needs to be updated for the P7, but nevertheless does a
pretty good job).
One interesting aspect of this change is that I've also enabled to use of AA
duing CodeGen for the P7 (just as it is for the embedded cores). The benchmark
results seem to support this decision (see below), and while this is normally
useful for in-order cores, and not for ooo cores like the P7, I think that the
dispatch slot hazards are enough like in-order resources to make the AA useful.
Test suite significant performance differences (where negative is a speedup,
and positive is a regression) vs. the current situation:
MultiSource/Benchmarks/BitBench/drop3/drop3
with AA: N/A
without AA: -28.7614% +/- 19.8356%
(significantly against AA)
MultiSource/Benchmarks/FreeBench/neural/neural
with AA: -17.7406% +/- 11.2712%
without AA: N/A
(significantly in favor of AA)
MultiSource/Benchmarks/SciMark2-C/scimark2
with AA: -11.2079% +/- 1.80543%
without AA: -11.3263% +/- 2.79651%
MultiSource/Benchmarks/TSVC/Symbolics-flt/Symbolics-flt
with AA: -41.8649% +/- 17.0053%
without AA: -34.5256% +/- 23.7072%
MultiSource/Benchmarks/mafft/pairlocalalign
with AA: 25.3016% +/- 17.8614%
without AA: 38.6629% +/- 14.9391%
(significantly in favor of AA)
MultiSource/Benchmarks/sim/sim
with AA: N/A
without AA: 13.4844% +/- 7.18195%
(significantly in favor of AA)
SingleSource/Benchmarks/BenchmarkGame/Large/fasta
with AA: 15.0664% +/- 6.70216%
without AA: 12.7747% +/- 8.43043%
SingleSource/Benchmarks/BenchmarkGame/puzzle
with AA: 82.2713% +/- 26.3567%
without AA: 75.7525% +/- 41.1842%
SingleSource/Benchmarks/Misc/flops-2
with AA: -37.1621% +/- 20.7964%
without AA: -35.2342% +/- 20.2999%
(significantly in favor of AA)
These are 99.5% confidence intervals from 5 runs per configuration. Regarding
the choice to turn on AA during CodeGen, of these results, four seem
significantly in favor of using AA, and one seems significantly against. I'm
not making this decision based on these numbers alone, but these results
seem consistent with results I have from other tests, and so I think that, on
balance, using AA is a win.
llvm-svn: 195981
2013-12-01 04:55:12 +08:00
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|
let Itineraries = P7Itineraries;
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}
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