Exploiting Parallelism Opportunities with Deep Learning Frameworks

Exploiting Parallelism Opportunities with Deep Learning Frameworks

13 August 2019

David Brooks

Papers citing "Exploiting Parallelism Opportunities with Deep Learning Frameworks"

5 / 5 papers shown

Title
Improving Inference Performance of Machine Learning with the Divide-and-Conquer Principle Alex Kogan LRM 21 0 0 12 Jan 2023
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems S. Farrell M. Emani J. Balma L. Drescher Aleksandr Drozd ... Akihiro Tabuchi V. Vishwanath M. Wahib Masafumi Yamazaki Junqi Yin VLM 32 35 0 21 Oct 2021
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference Jude Haris Perry Gibson José Cano Nicolas Bohm Agostini David Kaeli 41 19 0 01 Oct 2021
Optimizing Inference Performance of Transformers on CPUs D. Dice Alex Kogan 19 15 0 12 Feb 2021
Array Languages Make Neural Networks Fast Artjoms Šinkarovs Hans-Nikolai Vießmann S. Scholz 17 5 0 11 Dec 2019