REPTILES: Repeated Tiles of Sargantana, a RISC-V multicore based on OpenPiton

2026-05-06

AI Summary

This work addresses the challenge of balancing scalability and performance in open-source multicore processors for high-performance computing (HPC). To this end, the authors propose REPTILES, an open-source RISC-V multicore framework built upon OpenPiton. REPTILES integrates multiple Sargantana cores and employs a co-optimized design featuring a customized interconnect and memory hierarchy. The framework introduces key enhancements to both Sargantana and OpenPiton, significantly improving HPC application performance and scalability. Experimental results demonstrate that, in a 4-core configuration, REPTILES achieves an average speedup of 3.1× across benchmarks and delivers a 9.3× performance improvement on vector addition workloads.

Abstract

Chip industry continues advancing and expanding modern computing systems, resulting in more complex multi-core processors. Conversely, academic projects face scalability challenges due to limited resources, highlighting the need for open-source frameworks that enable innovation and knowledge sharing. Recently, several open-source proposals have emerged, offering flexible and scalable designs, but fail to meet the performance demands of modern High-Performance Computing (HPC) applications. In this project, we present REPTILES, an open-source RISC-V multicore framework based on OpenPiton\thanks. REPTILES interconnects multiple Sargantana cores with the memory hierarchy of OpenPiton. Moreover, we present the new features incorporated in Sargantana and OpenPiton designs to improve the performance of HPC applications. We demonstrate that REPTILES presents suitable scalability, achieving a speedup of 3.1x on average with 4 cores. Additionally, we show that Sargantana's new features increase the performance of vector addition benchmark in a 9.3x.

Problem

• open-source
• multicore
• RISC-V
• High-Performance Computing
• scalability

Innovation

• RISC-V
• multicore
• OpenPiton
• high-performance computing
• scalability