The slowdown of Moore's law and the power wall necessitates a shift toward finely tunable
precision (aka transprecision) computing to reduce energy footprint. Hence, we need circuits …

Coarse-Grained Reconfigurable Architectures (CGRAs) are being considered as a
complementary addition to modern High-Performance Computing (HPC) systems. These …

There is an emerging need to design configurable accelerators for the high-performance
computing (HPC) and artificial intelligence (AI) applications in different precisions. Thus, the …

There is an emerging need to design multi-precision floating-point (FP) accelerators for high-
performance-computing (HPC) applications. The commonly-used methods are based on …

Among the (uncontended) common wisdom in High-Performance Computing (HPC) is the
applications' need for large amount of double-precision support in hardware. Hardware …

In this paper, we present Faust, a pipelined FPU for vector processing-capable RISC-V core
developed within the European Processor Initiative (EPI) project. Faust is based on the open …

The dot-product is one of the most frequently used operations for a wide variety of high-
performance computing (HPC) and artificial intelligence (AI) applications. However, for large …

An era of exponentially improving computing efficiency is coming to an end as Moore's law
falters and Dennard scaling seems to have broken down. The power-wall obstacle fuels a …

We investigate the method of conjugate gradients, exploiting inaccurate matrix‐vector
products, for the solution of convex quadratic optimization problems. Theoretical …

High-performance computing (HPC) can facilitate deep neural network (DNN) training and
inference. Previous works have proposed multiple-precision floating-and fixed-point …