用于CERN高通量计算的小型SIMD矩阵

F. Lemaitre, Benjamin Couturier, L. Lacassagne
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引用次数: 4

摘要

系统跟踪是一个老问题,在过去已经进行了大量优化。然而,在高能物理中,许多小型系统都是使用卡尔曼滤波进行实时跟踪的,目前还没有满足这些约束的实现。在本文中,我们提出了一种用于加速小矩阵的乔列斯基分解和卡尔曼滤波的代码生成器。该生成器易于使用,并生成可移植且经过大量优化的代码。我们专注于当前的SIMD架构(SSE, AVX, AVX512, Neon, SVE, Altivec和VSX)。我们的Cholesky分解优于任何现有的库:比MKL快3到10倍。卡尔曼滤波器也比现有的实现更快,在2x24C英特尔至强处理器上达到4109 iter/s。
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Small SIMD Matrices for CERN High Throughput Computing
System tracking is an old problem and has been heavily optimized throughout the past. However, in High Energy Physics, many small systems are tracked in real-time using Kalman filtering and no implementation satisfying those constraints currently exists. In this paper, we present a code generator used to speed up Cholesky Factorization and Kalman Filter for small matrices. The generator is easy to use and produces portable and heavily optimized code. We focus on current SIMD architectures (SSE, AVX, AVX512, Neon, SVE, Altivec and VSX). Our Cholesky factorization outperforms any existing libraries: from x3 to x10 faster than MKL. The Kalman Filter is also faster than existing implementations, and achieves 4 · 109 iter/s on a 2x24C Intel Xeon.
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