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Advanced SIMD: Extending the reach of contemporary SIMD architectures

机译:先进的SIMD:扩展当代SIMD体系结构的范围

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SIMD extensions have gained widespread acceptance in modern microprocessors as a way to exploit data-level parallelism in general-purpose cores. Popular SIMD architectures (e.g. Intel SSE/AVX) have evolved by adding support for wider registers and datapaths, and advanced features like indexed memory accesses, per-lane predication and inter-lane instructions, at the cost of additional silicon area and design complexity. This paper evaluates the performance impact of such advanced features on a set of workloads considered hard to vectorize for traditional SIMD architectures. Their sensitivity to the most relevant design parameters (e.g. register/datapath width and L1 data cache configuration) is quantified and discussed. We developed an ARMv7 NEON based ISA extension (ARGON), augmented a cycle accurate simulation framework for it, and derived a set of benchmarks from the Berkeley dwarfs. Our analyses demonstrate how ARGON can, depending on the structure of an algorithm, achieve speedups of 1.5x to 16x.
机译:SIMD扩展已成为现代微处理器中广泛接受的一种方法,该方法可以利用通用内核中的数据级并行性。流行的SIMD架构(例如Intel SSE / AVX)通过增加对更广泛的寄存器和数据路径的支持以及诸如索引存储器访问,每通道谓词和通道间指令之类的高级功能而得到了发展,但同时却增加了芯片面积和设计复杂性。本文评估了这种高级功能对传统SIMD架构难以向量化的一组工作负载的性能影响。量化和讨论了它们对最相关的设计参数的敏感性(例如寄存器/数据路径宽度和L1数据高速缓存配置)。我们开发了基于ARMv7 NEON的ISA扩展(ARGON),为其增加了周期精确的仿真框架,并从伯克利侏儒派生了一组基准。我们的分析表明,根据算法的结构,ARGON如何实现1.5倍至16倍的加速。

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