![]() Still very interesting to compare the sequence of times results. Redeon58700, Execution time of test: 0.085571 s Over 1 gb and a benchmark over 0.80 (look in the CaptureICP. Pyopencl i5 CPU 750: Execution time of test: 0.00238112 s All 1GB and higher, OpenCL GPU should work. Pyopencl radeon 5870:Execution time of test: 0.0104431 s Pyopencl i5 CPU 750: Execution time of test: 4.369e-05 sįirst questions pack: what is pyopencl i5 CPU 750? why he faster "normal"('Execution time of test without OpenCL) in 250 times? and why he faster "pyopencl radeon 5870" in ~38 times? Pyopencl radeon 5870: Execution time of test: 0.00168922 s ('Platform vendor:', 'Advanced Micro Devices, Inc.') ![]() ('Platform name:', 'AMD Accelerated Parallel Processing') Print("Execution time of test: %g s" % elapsed)Ĭl.enqueue_read_buffer(queue, dest_buf, c).wait() _global const float *b, _global float *c)Įxec_evt = prg.sum(queue, a.shape, None, a_buf, b_buf, dest_buf)Įlapsed = 1e-9*(exec_ - exec_) Properties=cl.command_queue_properties.PROFILING_ENABLE)Ī_buf = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=a)ī_buf = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=b)ĭest_buf = cl.Buffer(ctx, mf.WRITE_ONLY, b.nbytes) Print("Device compute units:", device.max_compute_units) OpenCL support for AMD Radeon RX 7000 series hardware has been restored if using Adrenalin. GPU vendors like NVidia have no incentive to make sure their CPU-based OpenCL implementation is as fast as possible. Print("Device max clock speed:", device.max_clock_frequency, 'MHz') GPUPerfAPI provides access to GPU Performance Counters. Any benchmark either needs to list this time separately, use pre-compiled native kernels, or run long enough that the kernel compilation is insignificant. There are two program cpu.c and gpu. Print("Device memory: ", device.global_mem_size//1024//1024, 'MB') This is a simple test to compare the performance between CPU and GPU computation. Print("Device type:", cl.device_type.to_string(device.type)) Print("Platform version:", platform.version) Print("Platform vendor:", platform.vendor) Print("Platform profile:", platform.profile) Print("Execution time of test without OpenCL: ", time2 - time1, "s") On the horizon, OpenCL and the 13 Dwarves will likely be released soon, which could be useful for benchmarking purposes. Notable examples include the SHOC benchmark suite and Rodinia. ![]() Replaced by numbers, the variable zz import pyopencl as clĪ = (zz).astype(numpy.float32)ī = (zz).astype(numpy.float32)Ĭ_result = c_result * (a + b) Currently there is no set performance benchmarks to test speeds of different frameworks. I was a little modified the standard code from
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