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.6 percent of the original code was either auto-converted or left unmodified. Figure 2 compares the complexity of the Caffe HIP port with the port to OpenCL
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31.10.2017
along that Linux sysop sensibility when I joined the ROCm project.
AM: Isn’t OpenCL an open source solution that supports GPU acceleration?
GS: OpenCL is a solid solution; it solves a set of critical
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18.10.2017
supports Python Anaconda. Anaconda is a specialized version of Python tailored for scientific computing and large-scale data processing. ROCm also provides native support for the OpenCL (Open Compute
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05.11.2013
model, and thus the programming procedure, differs fundamentally from that of CPUs. As a consequence, existing programs cannot run directly on GPUs. Although the OpenCL parallel programming framework
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09.10.2013
can fit your problem into the CUDA or OpenCL parallelism model, this option can be very attractive.
A divergent yet equally powerful vision is Intel’s Xeon Phi coprocessor – better described as a Linux
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30.01.2013
language method or OpenCL, or maybe something built in that’s supplied by your vendor, you couldn’t get at the other eight SIMD lanes, or really seven – let’s say it had eight. You could only work through
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03.01.2013
or OpenCL to use it effectively. Listing 1 shows a code snippet taken from the main sciGPGU site that illustrates how to use the cuBLAS library. (Note that you can also used the cuFFT library, but sample
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. The programming tools are largely CUDA (NVidia hardware) and OpenCL (NVidia, AMD GPUs, and x86 multicore). These tools often require deep re-writing of exiting code to take advantage of GP-GPUs.The resultant code
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that runs on an accelerator. The most common example of an accelerator is a GPU, so instead of learning CUDA or OpenCL, you can just use directives and let the compiler do the heavy lifting.
Don
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use to tinker with HPC?
Many of the core HPC programming tools are often too low level for most domain specialists. Learning Fortran, C/C++, MPI, CUDA, or OpenCL is a tall order. These tools tend