VecIntrinBench: Benchmarking Cross-Architecture Intrinsic Code Migration for RISC-V Vector
Liutong Han, Chu Kang, Mingjie Xing, Yanjun Wu

TL;DR
This paper introduces VecIntrinBench, a comprehensive benchmark for evaluating intrinsic code migration to RISC-V Vector architecture, including 50 tasks and analysis of code migration approaches like LLMs and rule-based methods.
Contribution
It presents the first benchmark for RVV intrinsic migration, encompassing diverse tasks and enabling systematic evaluation of migration techniques.
Findings
LLMs perform comparably to rule-based methods for RISC-V code migration.
LLMs deliver superior performance in intrinsic code migration.
The benchmark is open-sourced for community use.
Abstract
Intrinsic functions are specialized functions provided by the compiler that efficiently operate on architecture-specific hardware, allowing programmers to write optimized code in a high-level language that fully exploits hardware features. Using intrinsics to vectorize core code blocks is a standard optimization method in high-performance libraries, often requiring specific vector optimization implementations for multiple mainstream architectures. The promising RISC-V software ecosystem has a significant demand for algorithm library migration and adaptation. Translating existing intrinsic functions to RISC-V Vector (RVV) intrinsic functions across architectures is currently a mainstream approach. Rule-based intrinsic mapping methods and LLM-based code generation can help developers address the code migration challenge. However, existing intrinsic code benchmarks focus on mainstream SIMD…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Embedded Systems Design Techniques · Logic, programming, and type systems
