Improve performance of inner_product #69
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Implemented simple kernel to perform inner_product, 10x performance gain
| type_name<product_type>() + " *c)\n" | ||
| "{\n" | ||
| " const uint i = get_global_id(0);\n" | ||
| " c[i] = a[i] * b[i];\n" |
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Should not this change decrease the performance? It looks like the original code accumulated the transformed sequence on the fly, and the new version stores the intermediate result to the global memory.
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There is an optimized accumulate/reduce() implementation which is used when the input iterators are buffer_iterator's and the function is commutative. This is most likely the cause for the performance increase.
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I see. So the best way to increase performance of inner_product (and probably of other operations and also user code) would be to optimize the implementation of accumulate for the transform iterators. accumulate should only read its input once, so I don't see why input being a buffer is important here?
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Accumulating the transformed sequence on the fly leads to a serial accumulation. As @kylelutz said, using a buffer eventually leads to reduce() or reduce_on_gpu() which is much faster.
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Yes, but the proposed variant uses four unnecessary global memory IO operations (write a, b, c, read c). I am sure this is the reason why it is still slower than the STL version. It should be easy to extend the parallel version of accumulate to work with generic random access iterators.
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Yeah, the proper long-term fix is to optimize accumulate/reduce for all input iterators, not just buffer_iterator.
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I've added an issue (#73) to fix the performance of accumulate() with InputIterators. I'll look into making the fix which should greatly improve the performance of current inner_product() implementation.
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Better fixed by issue #73. |
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I've updated @roshanr95: Can you try out the code from develop? |
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Working great!! ~160x performance increase from original. |
Implemented simple kernel to perform inner_product, 10x performance gain