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[llvm-profgen][NFC]Fix build failure on different platform see titile Test Plan: ninja & ninja check-llvm Reviewed By: hoy Differential Revision: https://reviews.llvm.org/D91897 2020-11-21 08:20:37 +08:00
[CSSPGO][llvm-profgen] Parse mmap events from perf script This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. As a starter, this change sets up an entry point by introducing PerfReader to load profiled binaries and perf traces(including perf events and perf samples). For the event, here it parses the mmap2 events from perf script to build the loader snaps, which is used to retrieve the image load address in the subsequent perf tracing parsing. As described in llvm-profgen.rst, the tool being built aims to support multiple input perf data (preprocessed by perf script) as well as multiple input binary images. It should also support dynamic reload/unload shared objects by leveraging the loader snaps being built by this change Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89707 2020-10-19 12:36:54 +08:00			`set(LLVM_LINK_COMPONENTS`
[CSSPGO][llvm-profgen] Disassemble text sections This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change enables disassembling the text sections to build various address maps that are potentially used by the virtual unwinder. A switch `--show-disassembly` is being added to print the disassembly code. Like the llvm-objdump tool, this change leverages existing LLVM components to parse and disassemble ELF binary files. So far X86 is supported. Test Plan: ninja check-llvm Reviewed By: wmi, wenlei Differential Revision: https://reviews.llvm.org/D89712 2020-10-20 01:02:05 +08:00			`AllTargetsDescs`
			`AllTargetsDisassemblers`
Fix shared build. 2020-11-22 06:06:41 +08:00			`AllTargetsInfos`
[CSSPGO][llvm-profgen] Parse mmap events from perf script This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. As a starter, this change sets up an entry point by introducing PerfReader to load profiled binaries and perf traces(including perf events and perf samples). For the event, here it parses the mmap2 events from perf script to build the loader snaps, which is used to retrieve the image load address in the subsequent perf tracing parsing. As described in llvm-profgen.rst, the tool being built aims to support multiple input perf data (preprocessed by perf script) as well as multiple input binary images. It should also support dynamic reload/unload shared objects by leveraging the loader snaps being built by this change Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89707 2020-10-19 12:36:54 +08:00			`Core`
[CSSPGO][llvm-profgen] Disassemble text sections This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change enables disassembling the text sections to build various address maps that are potentially used by the virtual unwinder. A switch `--show-disassembly` is being added to print the disassembly code. Like the llvm-objdump tool, this change leverages existing LLVM components to parse and disassemble ELF binary files. So far X86 is supported. Test Plan: ninja check-llvm Reviewed By: wmi, wenlei Differential Revision: https://reviews.llvm.org/D89712 2020-10-20 01:02:05 +08:00			`MC`
			`MCDisassembler`
			`Object`
[CSSPGO][llvm-profgen] Context-sensitive profile data generation This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change supports context-sensitive profile data generation into llvm-profgen. With simultaneous sampling for LBR and call stack, we can identify leaf of LBR sample with calling context from stack sample . During the process of deriving fall through path from LBR entries, we unwind LBR by replaying all the calls and returns (including implicit calls/returns due to inlining) backwards on top of the sampled call stack. Then the state of call stack as we unwind through LBR always represents the calling context of current fall through path. we have two types of virtual unwinding 1) LBR unwinding and 2) linear range unwinding. Specifically, for each LBR entry which can be classified into call, return, regular branch, LBR unwinding will replay the operation by pushing, popping or switching leaf frame towards the call stack and since the initial call stack is most recently sampled, the replay should be in anti-execution order, i.e. for the regular case, pop the call stack when LBR is call, push frame on call stack when LBR is return. After each LBR processed, it also needs to align with the next LBR by going through instructions from previous LBR's target to current LBR's source, which we named linear unwinding. As instruction from linear range can come from different function by inlining, linear unwinding will do the range splitting and record counters through the range with same inline context. With each fall through path from LBR unwinding, we aggregate each sample into counters by the calling context and eventually generate full context sensitive profile (without relying on inlining) to driver compiler's PGO/FDO. A breakdown of noteworthy changes: - Added `HybridSample` class as the abstraction perf sample including LBR stack and call stack * Extended `PerfReader` to implement auto-detect whether input perf script output contains CS profile, then do the parsing. Multiple `HybridSample` are extracted * Speed up by aggregating `HybridSample` into `AggregatedSamples` * Added VirtualUnwinder that consumes aggregated `HybridSample` and implements unwinding of calls, returns, and linear path that contains implicit call/return from inlining. Ranges and branches counters are aggregated by the calling context.  Here calling context is string type, each context is a pair of function name and callsite location info, the whole context is like `main:1 @ foo:2 @ bar`. * Added PorfileGenerater that accumulates counters by ranges unfolding or branch target mapping, then generates context-sensitive function profile including function body, inferring callee's head sample, callsite target samples, eventually records into ProfileMap.  * Leveraged LLVM build-in(`SampleProfWriter`) writer to support different serialization format with no stop - `getCanonicalFnName` for callee name and name from ELF section - Added regression test for both unwinding and profile generation Test Plan: ninja & ninja check-llvm Reviewed By: hoy, wenlei, wmi Differential Revision: https://reviews.llvm.org/D89723 2020-10-20 03:55:59 +08:00			`ProfileData`
[CSSPGO][llvm-profgen] Parse mmap events from perf script This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. As a starter, this change sets up an entry point by introducing PerfReader to load profiled binaries and perf traces(including perf events and perf samples). For the event, here it parses the mmap2 events from perf script to build the loader snaps, which is used to retrieve the image load address in the subsequent perf tracing parsing. As described in llvm-profgen.rst, the tool being built aims to support multiple input perf data (preprocessed by perf script) as well as multiple input binary images. It should also support dynamic reload/unload shared objects by leveraging the loader snaps being built by this change Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89707 2020-10-19 12:36:54 +08:00			`Support`
[CSSPGO][llvm-profgen] Instruction symbolization This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change adds the support of instruction symbolization. Given the RVA on an instruction pointer, a full calling context can be printed side-by-side with the disassembly code. E.g. ``` Disassembly of section .text [0x0, 0x4a]: <funcA>: 0: mov eax, edi funcA:0 2: mov ecx, dword ptr [rip] funcLeaf:2 @ funcA:1 8: lea edx, [rcx + 3] fib:2 @ funcLeaf:2 @ funcA:1 b: cmp ecx, 3 fib:2 @ funcLeaf:2 @ funcA:1 e: cmovl edx, ecx fib:2 @ funcLeaf:2 @ funcA:1 11: sub eax, edx funcLeaf:2 @ funcA:1 13: ret funcA:2 14: nop word ptr cs:[rax + rax] 1e: nop <funcLeaf>: 20: mov eax, edi funcLeaf:1 22: mov ecx, dword ptr [rip] funcLeaf:2 28: lea edx, [rcx + 3] fib:2 @ funcLeaf:2 2b: cmp ecx, 3 fib:2 @ funcLeaf:2 2e: cmovl edx, ecx fib:2 @ funcLeaf:2 31: sub eax, edx funcLeaf:2 33: ret funcLeaf:3 34: nop word ptr cs:[rax + rax] 3e: nop <fib>: 40: lea eax, [rdi + 3] fib:2 43: cmp edi, 3 fib:2 46: cmovl eax, edi fib:2 49: ret fib:8 ``` Test Plan: ninja check-llvm Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89715 2020-10-20 01:19:08 +08:00			`Symbolize`
[CSSPGO][llvm-profgen] Parse mmap events from perf script This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. As a starter, this change sets up an entry point by introducing PerfReader to load profiled binaries and perf traces(including perf events and perf samples). For the event, here it parses the mmap2 events from perf script to build the loader snaps, which is used to retrieve the image load address in the subsequent perf tracing parsing. As described in llvm-profgen.rst, the tool being built aims to support multiple input perf data (preprocessed by perf script) as well as multiple input binary images. It should also support dynamic reload/unload shared objects by leveraging the loader snaps being built by this change Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89707 2020-10-19 12:36:54 +08:00			`)`

			`add_llvm_tool(llvm-profgen`
			`llvm-profgen.cpp`
			`PerfReader.cpp`
[CSSPGO][llvm-profgen] Disassemble text sections This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change enables disassembling the text sections to build various address maps that are potentially used by the virtual unwinder. A switch `--show-disassembly` is being added to print the disassembly code. Like the llvm-objdump tool, this change leverages existing LLVM components to parse and disassemble ELF binary files. So far X86 is supported. Test Plan: ninja check-llvm Reviewed By: wmi, wenlei Differential Revision: https://reviews.llvm.org/D89712 2020-10-20 01:02:05 +08:00			`ProfiledBinary.cpp`
[CSSPGO][llvm-profgen] Context-sensitive profile data generation This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. This change supports context-sensitive profile data generation into llvm-profgen. With simultaneous sampling for LBR and call stack, we can identify leaf of LBR sample with calling context from stack sample . During the process of deriving fall through path from LBR entries, we unwind LBR by replaying all the calls and returns (including implicit calls/returns due to inlining) backwards on top of the sampled call stack. Then the state of call stack as we unwind through LBR always represents the calling context of current fall through path. we have two types of virtual unwinding 1) LBR unwinding and 2) linear range unwinding. Specifically, for each LBR entry which can be classified into call, return, regular branch, LBR unwinding will replay the operation by pushing, popping or switching leaf frame towards the call stack and since the initial call stack is most recently sampled, the replay should be in anti-execution order, i.e. for the regular case, pop the call stack when LBR is call, push frame on call stack when LBR is return. After each LBR processed, it also needs to align with the next LBR by going through instructions from previous LBR's target to current LBR's source, which we named linear unwinding. As instruction from linear range can come from different function by inlining, linear unwinding will do the range splitting and record counters through the range with same inline context. With each fall through path from LBR unwinding, we aggregate each sample into counters by the calling context and eventually generate full context sensitive profile (without relying on inlining) to driver compiler's PGO/FDO. A breakdown of noteworthy changes: - Added `HybridSample` class as the abstraction perf sample including LBR stack and call stack * Extended `PerfReader` to implement auto-detect whether input perf script output contains CS profile, then do the parsing. Multiple `HybridSample` are extracted * Speed up by aggregating `HybridSample` into `AggregatedSamples` * Added VirtualUnwinder that consumes aggregated `HybridSample` and implements unwinding of calls, returns, and linear path that contains implicit call/return from inlining. Ranges and branches counters are aggregated by the calling context.  Here calling context is string type, each context is a pair of function name and callsite location info, the whole context is like `main:1 @ foo:2 @ bar`. * Added PorfileGenerater that accumulates counters by ranges unfolding or branch target mapping, then generates context-sensitive function profile including function body, inferring callee's head sample, callsite target samples, eventually records into ProfileMap.  * Leveraged LLVM build-in(`SampleProfWriter`) writer to support different serialization format with no stop - `getCanonicalFnName` for callee name and name from ELF section - Added regression test for both unwinding and profile generation Test Plan: ninja & ninja check-llvm Reviewed By: hoy, wenlei, wmi Differential Revision: https://reviews.llvm.org/D89723 2020-10-20 03:55:59 +08:00			`ProfileGenerator.cpp`
[CSSPGO][llvm-profgen] Parse mmap events from perf script This stack of changes introduces `llvm-profgen` utility which generates a profile data file from given perf script data files for sample-based PGO. It’s part of(not only) the CSSPGO work. Specifically to support context-sensitive with/without pseudo probe profile, it implements a series of functionalities including perf trace parsing, instruction symbolization, LBR stack/call frame stack unwinding, pseudo probe decoding, etc. Also high throughput is achieved by multiple levels of sample aggregation and compatible format with one stop is generated at the end. Please refer to: https://groups.google.com/g/llvm-dev/c/1p1rdYbL93s for the CSSPGO RFC. As a starter, this change sets up an entry point by introducing PerfReader to load profiled binaries and perf traces(including perf events and perf samples). For the event, here it parses the mmap2 events from perf script to build the loader snaps, which is used to retrieve the image load address in the subsequent perf tracing parsing. As described in llvm-profgen.rst, the tool being built aims to support multiple input perf data (preprocessed by perf script) as well as multiple input binary images. It should also support dynamic reload/unload shared objects by leveraging the loader snaps being built by this change Reviewed By: wenlei, wmi Differential Revision: https://reviews.llvm.org/D89707 2020-10-19 12:36:54 +08:00			`)`