Journal Article

Variable and Extended Precision (VRP) Accelerator Implemented in a 22 nm SoC

Fereyre, Jérôme, Bocco, Andrea, Guthmuller, Eric, Evans, Adrian, Fuguet, César, Durand, Yves

2025

Overview

Linear solvers and eigensolvers are the heart of high‐performance computing scientific applications. Among them, iterative projection methods are preferred to direct algorithms for large problems because of their lower memory usage, but they are prone to roundoff errors. Using an enhanced working precision inside the linear computing kernels mitigates this issue and accelerates convergence. Today, to go beyond 80 bits of precision, the only option is to use software libraries which are very slow. We introduce the variable and extended precision accelerator (VRP), a RISC‐V accelerator implemented on a system‐on‐chip (SoC) using GF22FDX technology. The VRP supports floating point computations with a range of significand bits from 2 to 512. This accelerator delivers an average 19.25× $\\times$application speedup compared to the well‐known MPFR software library running on a 2400 MHz Intel Xeon processor. Additionally, extended precision facilitates the convergence of linear solvers for problems that would otherwise fail to converge and reduces energy‐to‐solution. We implemented a variable extended precision accelerator, with support of up to 512‐bit precision, in a 22 nm system‐on‐chip. We demonstrate its ability to improve convergence of linear solver by running conjugate gradient methods on the chip at 800 MHz working frequency. By measuring power consumption, we demonstrate that extended precision not only has the potential to improve time‐to‐solution, but also energy‐to‐solution on difficult‐to‐solve scientific computing problems.

• Publisher: IET
• Subject: circuits and systems / CMOS integrated circuits / Computer Arithmetic / Computer Science / coprocessors / floating point arithmetic / Hardware Architecture / microprocessor chips