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Improved Memory Operations #174
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Closes #172 Co-authored-by: Takuya Hashimoto <toge@users.noreply.github.com>
On the Leipzig1M dataset, LibC vs SZ: ~ 128b lines, aligned: 2.3 vs 2.6 GB/s ~ 128b lines, unaligned: 2.34 vs 2.53 GB/s ~ 5b tokens, aligned: 0.1 vs 0.1 GB/s ~ 5b tokens, unaligned: 0.1 vs 0.1 GB/s ~ 124 MB, aligned: 19.6 vs 20.3 GB/s ~ 124 MB, unaligned: 19.6 vs 20.3 GB/s
Previously SZ would build too many targets for each debugging session.
This commit accelerates the `sz_fill_avx2` and `sz_copy_avx2` by avoiding unaligned writes. It also adds an `sz_equal_avx2` to help validate large files with matching checksums faster. It also adds a placeholder for `sz_order_avx2`, discouraging further optimizations. C++ API with a matching argument order was added to mimic `std::memcpy`, `std::memset`, `std::memmove`. Matching `test_memory_utilities` tests were extended.
In AVX-512, similar to GLibC we should use the register space to load more data simultaneously and avoid loops and data-dependency between iterations.
The new `sz_look_up_transform` API implements a 256-byte lookup table using serial code and AVX-512 that can significantly accelerates text and image processing. The AVX-512 implementation reaches 18 GB/s on Intel Sapphire Rapids CPU, while serial code stays around 3 GB/s for large files.
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This update brings many performance optimizations before the next wave of breaking major releases with new functionality and wider range of CPUs supported. Time to get excited 🥳
Faster
memcpy
andmemset
On Intel Sapphire Rapids:
On AWS Graviton 4 we still have room for improvement.
A potential improvement can come from non-temporal stores on large payloads.
256-byte Look-Up Table Transform
On Intel Sapphire Rapids:
On AWS Graviton 4: