121 citations · 230 across the 13 of their papers we have counts for
3 papers · 1 filter
Evaluation of POSIT Arithmetic with Accelerators
Naohito Nakasato, Yuki Murakami, Fumiya Kono +1
We present an evaluation of 32-bit POSIT arithmetic through its implementation as accelerators on FPGAs and GPUs. POSIT, a floating-point number format, adaptively changes the size…
Accelerating 128-bit Floating-Point Matrix Multiplication on FPGAs
Fumiya Kono, Naohito Nakasato, Maho Nakata
General Matrix Multiplication (GEMM) is a fundamental operation widely used in scientific computations. Its performance and accuracy significantly impact the performance and accura…
White Paper from Workshop on Large-scale Parallel Numerical Computing Technology (LSPANC 2020): HPC and Computer Arithmetic toward Minimal-Precision Computing
Roman Iakymchuk, Daichi Mukunoki, Artur Podobas +15
In numerical computations, precision of floating-point computations is a key factor to determine the performance (speed and energy-efficiency) as well as the reliability (accuracy…