Useful links¶
Document |
Description |
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Documentation for programming NumPy-like codes on data parallel devices |
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Documentation for programming Numba codes on data parallel devices the same way as you program Numba on CPU |
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Documentation how to manage data and devices, how to interchange data between different tensor implementations, and how to write data parallel extensions |
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Performance profiler supporting analysis of bottlenecks from function leve down to low level instructions. Supports Python and Numba |
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Analyzes native and Python codes and provides an advice for better composition of heterogeneous algorithms |
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Standard for writing portable Numpy-like codes targeting different hardware vendors and frameworks operating with tensor data |
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Standard for writing C++-like codes for heterogeneous computing |
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Free e-book how to program data parallel devices using Data Parallel C++ |
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OpenCl* Standard for heterogeneous programming |
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Standard for floating-point arithmetic, essential for writing robust numerical codes |
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Documentation for Numpy - foundational CPU library for array programming. Used in conjunction with Data Parallel Extension for Numpy*. |
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Documentation for Numba - Just-In-Time compiler for Numpy-like codes. Used in conjunction with Data Parallel Extension for Numba*. |