Caffe* Optimized for Intel® Architecture: Applying Modern Code Techniques

This paper demonstrates a special version of Caffe* — a deep learning framework originally developed by the Berkeley Vision and Learning Center (BVLC) — that is optimized for Intel® architecture.
作者: 最后更新时间: 2019/07/06 - 16:40

Hybrid Parallelism: A MiniFE* Case Study

This case study examines the situation where the problem decomposition is the same for threading as it is for Message Passing Interface* (MPI); that is, the threading parallelism is elevated to the same level as MPI parallelism.
作者: David M. 最后更新时间: 2019/07/06 - 16:40

Something Old to be New Again?

In the past couple of years I've noticed a trend to "re-invent" technology or re-brand old ideas and concepts from previous computing generations.

作者: Clay B. (Blackbelt) 最后更新时间: 2019/03/05 - 23:48

The Unfairness of Good Syntax

The unfairness of good syntax - bad syntax is a problem; good syntax is not a solution.
作者: 最后更新时间: 2019/07/04 - 11:17

Performance of Classic Matrix Multiplication Algorithm on Intel® Xeon Phi™ Processor System

Matrix multiplication (MM) of two matrices is one of the most fundamental operations in linear algebra. The algorithm for MM is very simple, it could be easily implemented in any programming language. This paper shows that performance significantly improves when different optimization techniques are applied.
作者: 最后更新时间: 2019/06/14 - 11:50

Big Datasets from Small Experiments

作者: Andrey Vladimirov 最后更新时间: 2019/07/04 - 18:46

Brain Development Simulation, 300x Faster

作者: Andrey Vladimirov 最后更新时间: 2019/07/04 - 17:45

Track Reconstruction with Deep Learning at the CERN CMS Experiment

Connecting the Dots
作者: 最后更新时间: 2018/12/12 - 18:00