Characterizing and Optimizing Realistic Workloads on a Commercial...

Compute-in-SRAM architectures offer a promising approach to achieving higher performance and energy efficiency across a range of data-intensive applications. However, prior evaluations have largely relied on simulators or small prototypes, limiting the understanding of their…

Multilingual and Multimodal Vector Search with Hardware Acceleration

Authors: Dmitry Kan, Aarne Talman

NeurIPS 2021 Announcement: The Billion-Scale Approximate Nearest Neighbor Search Challenge

We are excited to announce that this year’s NeurIPS 2021 Conference will host a first-of-its-kind competition in large scale approximate…

High-Performance, Billion-Scale Similarity Search | by Pat Lasserre | GSI T

In Part 1 of this series, we introduced the concept of embedding vectors. In Part 2, we discussed how embedding vectors can be used in…

RE•WORK Deep Learning Summit, San Francisco 2017 In-Place Computing: High-P