GPU Parallel Program Development Using CUDA by Tolga Soyata
This book teaches GPU programming by introducing CPU multi-threaded programming and bases GPU massively-parallel programming on this foundation. The differences among families of GPUs are also studied. The book also explores CUDA libraries, OpenCL, GPU programming with other languages and API libraries, and the deep learning library cuDNN.-
Fundamentals of Multicore Software Development
-
Methods and Applications of Autonomous Experimentation
-
The Green Computing Book
-
High Performance Computing
-
Peer-to-Peer Computing
-
Contemporary High Performance Computing
-
Introduction to the Simulation of Dynamics Using Simulink
-
Introduction to Scheduling
-
Introduction to Reversible Computing
-
Grid Computing
-
The End of Error
-
Software Engineering for Science
-
Parallel Programming with Co-arrays
-
Scientific Computing with Multicore and Accelerators
-
Data-Intensive Science
-
Introduction to Modeling and Simulation with MATLAB (R) and Python
-
Introduction to Computational Models with Python
-
Every Bit Counts
-
Introduction to High Performance Computing for Scientists and Engineers
-
Elements of Parallel Computing
-
Fundamentals of Parallel Multicore Architecture
-
Programming for Hybrid Multi/Manycore MPP Systems
-
Computational Methods in Plasma Physics
-
Unmatched
Tolga Soyata is an associate professor in the Electrical and Computer Engineering department of SUNY Albany.
| SKU | Unavailable |
| ISBN 13 | 9781498750752 |
| ISBN 10 | 1498750753 |
| Title | GPU Parallel Program Development Using CUDA |
| Author | Tolga Soyata |
| Series | Chapman And Hall Crc Computational Science |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Taylor & Francis Inc |
| Year published | 2018-02-16 |
| Number of pages | 476 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |