CULA: hybrid GPU accelerated linear algebra routines

John R. Humphrey; Daniel K. Price; Kyle E. Spagnoli; Aaron L. Paolini; Eric J. Kelmelis

doi:10.1117/12.850538

26 April 2010 CULA: hybrid GPU accelerated linear algebra routines

John R. Humphrey, Daniel K. Price, Kyle E. Spagnoli, Aaron L. Paolini, Eric J. Kelmelis

Proceedings Volume 7705, Modeling and Simulation for Defense Systems and Applications V; 770502 (2010) https://doi.org/10.1117/12.850538
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

The modern graphics processing unit (GPU) found in many standard personal computers is a highly parallel math processor capable of nearly 1 TFLOPS peak throughput at a cost similar to a high-end CPU and an excellent FLOPS/watt ratio. High-level linear algebra operations are computationally intense, often requiring O(N³) operations and would seem a natural fit for the processing power of the GPU. Our work is on CULA, a GPU accelerated implementation of linear algebra routines. We present results from factorizations such as LU decomposition, singular value decomposition and QR decomposition along with applications like system solution and least squares. The GPU execution model featured by NVIDIA GPUs based on CUDA demands very strong parallelism, requiring between hundreds and thousands of simultaneous operations to achieve high performance. Some constructs from linear algebra map extremely well to the GPU and others map poorly. CPUs, on the other hand, do well at smaller order parallelism and perform acceptably during low-parallelism code segments. Our work addresses this via hybrid a processing model, in which the CPU and GPU work simultaneously to produce results. In many cases, this is accomplished by allowing each platform to do the work it performs most naturally.

Citation Download Citation

John R. Humphrey, Daniel K. Price, Kyle E. Spagnoli, Aaron L. Paolini, and Eric J. Kelmelis "CULA: hybrid GPU accelerated linear algebra routines", Proc. SPIE 7705, Modeling and Simulation for Defense Systems and Applications V, 770502 (26 April 2010); https://doi.org/10.1117/12.850538

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available