33 citations · 85 across the 7 of their papers we have counts for
7 papers
MIRGE: An Array-Based Computational Framework for Scientific Computing
Matthias Diener, Matthew J. Smith, Michael T. Campbell +6
MIRGE is a computational approach for scientific computing based on NumPy-like array computation, but using lazy evaluation to recast computation as data-flow graphs, where nodes r…
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…
The LDBC Graphalytics Benchmark
Alexandru Iosup, Ahmed Musaafir, Alexandru Uta +15
In this document, we describe LDBC Graphalytics, an industrial-grade benchmark for graph analysis platforms. The main goal of Graphalytics is to enable the fair and objective compa…
High-Performance Deep Learning via a Single Building Block
Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar +6
Deep learning (DL) is one of the most prominent branches of machine learning. Due to the immense computational cost of DL workloads, industry and academia have developed DL librari…
ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler
Matthew Sotoudeh, Anand Venkat, Michael Anderson +3
Domain specific accelerators present new challenges and opportunities for code generation onto novel instruction sets, communication fabrics, and memory architectures. In this pape…
BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies
Shihao Ji, S. V. N. Vishwanathan, Nadathur Satish +2
We propose BlackOut, an approximation algorithm to efficiently train massive recurrent neural network language models (RNNLMs) with million word vocabularies. BlackOut is motivated…
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…