4 papers
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…
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…
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,…
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…