438 citations · 505 across the 5 of their papers we have counts for
7 papers
First-Generation Inference Accelerator Deployment at Facebook
Michael Anderson, Benny Chen, Stephen Chen +112
In this paper, we provide a deep dive into the deployment of inference accelerators at Facebook. Many of our ML workloads have unique characteristics, such as sparse memory accesse…
Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
Jongsoo Park, Maxim Naumov, Protonu Basu +25
The application of deep learning techniques resulted in remarkable improvement of machine learning models. In this paper provides detailed characterizations of deep learning models…
Glow: Graph Lowering Compiler Techniques for Neural Networks
Nadav Rotem, Jordan Fix, Saleem Abdulrasool +15
This paper presents the design of Glow, a machine learning compiler for heterogeneous hardware. It is a pragmatic approach to compilation that enables the generation of highly opti…
Galactos: Computing the Anisotropic 3-Point Correlation Function for 2 Billion Galaxies
Brian Friesen, Md. Mostofa Ali Patwary, Brian Austin +8
The nature of dark energy and the complete theory of gravity are two central questions currently facing cosmology. A vital tool for addressing them is the 3-point correlation funct…
Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data
Thorsten Kurth, Jian Zhang, Nadathur Satish +12
This paper presents the first, 15-PetaFLOP Deep Learning system for solving scientific pattern classification problems on contemporary HPC architectures. We develop supervised conv…
GraphMat: High performance graph analytics made productive
Narayanan Sundaram, Nadathur Rajagopalan Satish, Md Mostofa Ali Patwary +4
Given the growing importance of large-scale graph analytics, there is a need to improve the performance of graph analysis frameworks without compromising on productivity. GraphMat…