mirror of https://github.com/silx-kit/pyFAI.git
benchmark for size
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@ -73,7 +73,6 @@ None_buf = pyopencl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=numpy.z
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outData_buf = pyopencl.Buffer(ctx, mf.WRITE_ONLY, numpy.dtype("float32").itemsize * bins)
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outCount_buf = pyopencl.Buffer(ctx, mf.WRITE_ONLY, numpy.dtype("float32").itemsize * bins)
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outMerge_buf = pyopencl.Buffer(ctx, mf.WRITE_ONLY, numpy.dtype("float32").itemsize * bins)
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kernel = program.all_kernels()[0]
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args = (weights_buf,
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numpy.uint32(2048),
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numpy.uint32(integ.lut_size),
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@ -90,7 +89,7 @@ args = (weights_buf,
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outCount_buf,
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outMerge_buf)
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t4 = time.time()
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program.lut_integrate(q, (bins,), *args)
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program.lut_integrate(q, (bins,), (64,), *args)
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b = numpy.empty(bins, dtype=numpy.float32)
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c = numpy.empty(bins, dtype=numpy.float32)
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d = numpy.empty(bins, dtype=numpy.float32)
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@ -100,6 +99,12 @@ pyopencl.enqueue_read_buffer(q, outMerge_buf, b).wait()
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t5 = time.time()
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print "OpenCL speed-up: %s setup:%s exec %s" % (ref_time / (t5 - t3), t4 - t3, t5 - t4)
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print abs(ra - a).max(), abs(rb - b).max(), abs(rc - c).max(), abs(rd - d).max()
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for i in range(10):
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j = 2 ** i
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st = time.time()
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program.lut_integrate(q, (bins,), (j,), *args)
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pyopencl.enqueue_read_buffer(q, outMerge_buf, b).wait()
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print("Size: %s \ttime: %.2fms" % (j, 1000 * (time.time() - st)))
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#plot(ee)
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pylab.plot(a, b, label="OpenCL")
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