Problem
Research questions and friction points this paper is trying to address.
RISC-V
High Performance Computing
Poisson operator
data transposition
performance bottleneck
Exploring spectral element methods on the Tenstorrent RISC-V accelerator
🤖 AI Summary
研究在Tenstorrent RISC-V加速器上移植Nekbone的AX内核，通过优化数据转置提高性能，超越了24核Xeon Platinum CPU，并显著降低了功耗。
📝 Abstract
The growing availability of commodity RISC-V hardware has sparked interest in its use for High Performance Computing (HPC), with PCIe accelerator cards offering a practical near-term pathway to adoption. The Tenstorrent Wormhole is one example, with dedicated vector and matrix units across 128 Tensix cores, and is widely available. In this paper, we explore porting the AX kernel of Nekbone, a widely used HPC mini-application derived from the Gordon Bell Prize-winning Nek5000 spectral element solver, onto the Wormhole accelerator. This kernel evaluates the Poisson operator, and we describe the mapping of the algorithm onto the Tensix. The initial performance results reveal that the host-side data transposition, required for the z-direction gradient computation, is a severe bottleneck. Consequently, we investigated two optimisation strategies that yield dramatic improvements, achieving 242.97 GFLOPS for 100000 elements across 128 Tensix cores, outperforming a 24-core Xeon Platinum CPU and drawing approximately 7 times less power.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Spectral Element Methods
RISC-V Accelerator
Data Transposition Optimization
High Performance Computing
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
