activity
20222026
most citedRecovering single precision accuracy from Tensor Cores while surpassing the FP32 theoretical peak performance

43 citations · 47 across the 6 of their papers we have counts for

collaborators

7 papers

math.NA2026

Mixed-Precision Computing for Scientific Discovery: Formats, Co-Design, and Responsible Approximation

Emmanuel Agullo, Hartwig Anzt, Daniel Bauer +37

Reduced and mixed precision have moved from a niche optimization to a central design axis in scientific computing and engineering, driven by energy constraints, heterogeneous accel…

cs.DC2023

Reducing shared memory footprint to leverage high throughput on Tensor Cores and its flexible API extension library

Hiroyuki Ootomo, Rio Yokota

NVIDIA Tensor Core is a mixed-precision matrix-matrix multiplication and addition computing unit, where the theoretical peak performance is more than 300 TFlop/s on NVIDIA A100 GPU…

cs.DS2023★ 2 cited

CAGRA: Highly Parallel Graph Construction and Approximate Nearest Neighbor Search for GPUs

Hiroyuki Ootomo, Akira Naruse, Corey Nolet +3

Approximate Nearest Neighbor Search (ANNS) plays a critical role in various disciplines spanning data mining and artificial intelligence, from information retrieval and computer vi…

cs.DC2023★ 1 cited

DGEMM on Integer Matrix Multiplication Unit

Hiroyuki Ootomo, Katsuhisa Ozaki, Rio Yokota

Deep learning hardware achieves high throughput and low power consumption by reducing computing precision and specializing in matrix multiplication. For machine learning inference,…

cs.DC2023

Mixed-Precision Random Projection for RandNLA on Tensor Cores

Hiroyuki Ootomo, Rio Yokota

Random projection can reduce the dimension of data while capturing its structure and is a fundamental tool for machine learning, signal processing, and information retrieval, which…

cs.DC2023★ 1 cited

Custom 8-bit floating point value format for reducing shared memory bank conflict in approximate nearest neighbor search

Hiroyuki Ootomo, Akira Naruse

The k-nearest neighbor search is used in various applications such as machine learning, computer vision, database search, and information retrieval. While the computational cost of…

cs.DC2022★ 43 cited

Recovering single precision accuracy from Tensor Cores while surpassing the FP32 theoretical peak performance

Hiroyuki Ootomo, Rio Yokota

Tensor Core is a mixed-precision matrix-matrix multiplication unit on NVIDIA GPUs with a theoretical peak performance of more than 300 TFlop/s on Ampere architectures. Tensor Cores…