Häftad, Engelska, 2026
Programming Massively Parallel Processors
A Hands-on Approach
Av Wen-mei W. Hwu, David B. Kirk, Izzat El Hajj
969 kr
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Beskrivning
- Expanded optimization checklist with a more comprehensive demonstration of essential optimizations across patterns
- New pattern and application chapters including: filtering, wavefront parallelism, advanced optimizations for matrix multiplication, and large language models (LLMs)
- More coverage of important CUDA features including warp-level programming, cooperative groups, CUDA C++ atomics, and multi-GPU programming with NCCL and NVSHMEM
Produktinformation
- Utgivningsdatum: 2026-06-02
- Mått: 208 x 27 x 189 mm
- Vikt: 1 105 g
- Format: Häftad
- Språk: Engelska
- Antal sidor: 680
- Upplaga: 5
- Förlag: Elsevier Science
- ISBN: 9780443439001
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Wen-mei W. Hwuis a Senior Director of Research of NVIDIA and the Sanders-AMD Endowed Chair Professor Emeritus of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His work focuses on parallel computing—covering architecture, implementation, compilers, and algorithms. Dr. Hwu has received numerous honors, including the ACM/IEEE Eckert-Mauchly Award, ACM Grace Murray Hopper Award, IEEE B.R. Rau Award. He is an IEEE and ACM Fellow. He earned his Ph.D. in Computer Science from UC Berkele David B. Kirkis known for major contributions to graphics, hardware, and algorithms. Before pursuing his Ph.D. at Caltech, he earned B.S. and M.S. degrees in mechanical engineering from MIT and worked at Raster Technologies and Hewlett-Packard’s Apollo Systems Division. After completing his doctorate, he served as chief scientist and head of technology at Crystal Dynamics. In 1997, he became Chief Scientist at NVIDIA. Dr. Kirk has received numerous honors including the IEEE Seymour Cray Computer Engineering Award and ACM SIGGRAPH Computer Graphics Achievement Award. He is a member of the U.S. National Academy of Engineering. Izzat El Hajjis an Assistant Professor of Computer Science at the American University of Beirut. His research focuses on leveraging accelerator architectures to tackle challenging computations, with a focus on GPU computing, processing-in-memory, and performance modeling. He earned his Ph.D. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He has received the Dan Vivoli Endowed Fellowship (UIUC) and the Distinguished Graduate Award from the American University of Beirut.
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