Scaling up matrix computations on shared-memory manycore systems with 1000 CPU cores

By Fengguang Song, Jack J. Dongarra. 2014

13 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Hardware and Architecture, ML Systems & Hardware, Numerical Methods & Scientific Computing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Christian Szegedy
2. Vincent Vanhoucke
3. Andrew Rabinovich
4. Yangqing Jia
5. Wei David Liu
6. Xiangnan He
7. Tat-seng Chua

In Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Xiaogang Wang
3. Dacheng Tao
4. Trevor Darrell
5. Jitendra Malik
6. Andrew Zisserman
7. Alan L. Yuille
8. Ming-Hsuan Yang

In Hardware and Architecture

1. Christian Szegedy
2. Vincent Vanhoucke
3. Yangqing Jia

In ML Systems & Hardware

1. Vincent Vanhoucke

In Numerical Methods & Scientific Computing

1. Christian Szegedy
2. Andrew Rabinovich
3. Wei David Liu

Citations in the corpus

• Going deeper with convolutions (2014, background): “The gap is widened yet further by the use of steadily improving and highly tuned numerical libraries that allow for extremely fast dense matrix multiplication, exploiting the minute details of the underlying CPU or GPU hardware [16, 9].”