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Intel has recently updated its open-source C++ header file library for high-performance SIMD-based sorting to support the AVX-512 SIMD instruction set. Extending the capability of regular AVX2 support, the sorting functions now implement 512-bit extensions to offer greater performance. According to Phoronix, the NumPy Python library for mathematics that underpins a lot of software has updated its software base to use the AVX-512 boosted sorting functionality that yields a fantastic uplift in performance. The library uses AVX-512 to vectorize the quicksort for 16-bit and 64-bit data types using the extended instruction set. Benchmarked on an Intel Tiger Lake system, the NumPy sorting saw a 10-17x increase in performance.
Intel's engineer Raghuveer Devulapalli changed the NumPy code, which was merged into the NumPy codebase on Wednesday. Regarding individual data types, the new implementation increases 16-bit int sorting by 17x and 32-bit data type sorting by 12-13x, while float 64-bit sorting for random arrays has experienced a 10x speed up. Using the x86-simd-sort code, this speed-up shows the power of AVX-512 and its capability to enhance the performance of various libraries. We hope to see more implementations of AVX-512, as AMD has joined the party by placing AVX-512 processing elements on Zen 4.
View at TechPowerUp Main Site | Source
Intel's engineer Raghuveer Devulapalli changed the NumPy code, which was merged into the NumPy codebase on Wednesday. Regarding individual data types, the new implementation increases 16-bit int sorting by 17x and 32-bit data type sorting by 12-13x, while float 64-bit sorting for random arrays has experienced a 10x speed up. Using the x86-simd-sort code, this speed-up shows the power of AVX-512 and its capability to enhance the performance of various libraries. We hope to see more implementations of AVX-512, as AMD has joined the party by placing AVX-512 processing elements on Zen 4.
View at TechPowerUp Main Site | Source