Blog post

Track Reconstruction with Deep Learning at the CERN CMS Experiment

Connecting the Dots
Authored by Last updated on 12/12/2018 - 18:00
Blog post

Track Reconstruction with Deep Learning at the CERN CMS Experiment

This blog post is part of a series that describes my summer school project at CERN openlab.

Authored by Last updated on 09/30/2019 - 16:50
Article

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.
Authored by Last updated on 10/15/2019 - 15:30
Article

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.
Authored by Last updated on 10/15/2019 - 15:30
Article

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.
Authored by David M. Last updated on 10/15/2019 - 16:40
Article

Thread Parallelism in Cython*

Cython* is a superset of Python* that additionally supports C functions and C types on variable and class attributes. Cython generates C extension modules, which can be used by the main Python program using the import statement.
Authored by Nguyen, Loc Q (Intel) Last updated on 10/15/2019 - 16:40