Efficient Architecture for RISC-V Vector Memory Access

Fuente: arXiv
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Auteurs principaux: Guan, Hongyi, Gao, Yichuan, Miao, Chenlu, Wu, Haoyang, Zhu, Hang, Lin, Mingfeng, Liang, Huayue
Format: Preprint
Publié: 2025
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author Guan, Hongyi
Gao, Yichuan
Miao, Chenlu
Wu, Haoyang
Zhu, Hang
Lin, Mingfeng
Liang, Huayue
author_facet Guan, Hongyi
Gao, Yichuan
Miao, Chenlu
Wu, Haoyang
Zhu, Hang
Lin, Mingfeng
Liang, Huayue
contents Vector processors frequently suffer from inefficient memory accesses, particularly for strided and segment patterns. While coalescing strided accesses is a natural solution, effectively gathering or scattering elements at fixed strides remains challenging. Naive approaches rely on high-overhead crossbars that remap any byte between memory and registers, leading to physical design issues. Segment operations require row-column transpositions, typically handled using either element-level in-place transposition (degrading performance) or large buffer-based bulk transposition (incurring high area overhead). In this paper, we present EARTH, a novel vector memory access architecture designed to overcome these challenges through shifting-based optimizations. For strided accesses, EARTH integrates specialized shift networks for gathering and scattering elements. After coalescing multiple accesses within the same cache line, data is routed between memory and registers through the shifting network with minimal overhead. For segment operations, EARTH employs a shifted register bank enabling direct column-wise access, eliminating dedicated segment buffers while providing high-performance, in-place bulk transposition. Implemented on FPGA with Chisel HDL based on an open-source RISC-V vector unit, EARTH enhances performance for strided memory accesses, achieving 4x-8x speedups in benchmarks dominated by strided operations. Compared to conventional designs, EARTH reduces hardware area by 9% and power consumption by 41%, significantly advancing both performance and efficiency of vector processors.
format Preprint
id arxiv_https___arxiv_org_abs_2504_08334
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Efficient Architecture for RISC-V Vector Memory Access
Guan, Hongyi
Gao, Yichuan
Miao, Chenlu
Wu, Haoyang
Zhu, Hang
Lin, Mingfeng
Liang, Huayue
Hardware Architecture
Distributed, Parallel, and Cluster Computing
Vector processors frequently suffer from inefficient memory accesses, particularly for strided and segment patterns. While coalescing strided accesses is a natural solution, effectively gathering or scattering elements at fixed strides remains challenging. Naive approaches rely on high-overhead crossbars that remap any byte between memory and registers, leading to physical design issues. Segment operations require row-column transpositions, typically handled using either element-level in-place transposition (degrading performance) or large buffer-based bulk transposition (incurring high area overhead). In this paper, we present EARTH, a novel vector memory access architecture designed to overcome these challenges through shifting-based optimizations. For strided accesses, EARTH integrates specialized shift networks for gathering and scattering elements. After coalescing multiple accesses within the same cache line, data is routed between memory and registers through the shifting network with minimal overhead. For segment operations, EARTH employs a shifted register bank enabling direct column-wise access, eliminating dedicated segment buffers while providing high-performance, in-place bulk transposition. Implemented on FPGA with Chisel HDL based on an open-source RISC-V vector unit, EARTH enhances performance for strided memory accesses, achieving 4x-8x speedups in benchmarks dominated by strided operations. Compared to conventional designs, EARTH reduces hardware area by 9% and power consumption by 41%, significantly advancing both performance and efficiency of vector processors.
title Efficient Architecture for RISC-V Vector Memory Access
topic Hardware Architecture
Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2504.08334