GPU Computing Gems Emerald Edition (Hardcover)
Wen-mei W. Hwu
- 出版商: Morgan Kaufmann
- 出版日期: 2011-01-24
- 售價: $1,800
- 貴賓價: 9.5 折 $1,710
- 語言: 英文
- 頁數: 886
- 裝訂: Hardcover
- ISBN: 0123849888
- ISBN-13: 9780123849885
-
相關分類:
GPU
立即出貨
買這商品的人也買了...
-
$880$695 -
$1,890$1,796 -
$2,490$2,366 -
$530$451 -
$1,570$1,492 -
$860$731 -
$420$357 -
$520$442 -
$820$697 -
$530$419 -
$750$638 -
$450$351 -
$680$578 -
$450$383 -
$520$442 -
$850$672 -
$580$493 -
$750$638 -
$950$751 -
$590$466 -
$450$351 -
$2,480$2,356 -
$1,600$1,520 -
$580$493 -
$440$374
商品描述
".the perfect companion to Programming Massively Parallel Processors by Hwu & Kirk." -Nicolas Pinto, Research Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010
Graphics processing units (GPUs) can do much more than render graphics. Scientists and researchers increasingly look to GPUs to improve the efficiency and performance of computationally-intensive experiments across a range of disciplines.
GPU Computing Gems: Emerald Edition brings their techniques to you, showcasing GPU-based solutions including:
- Black hole simulations with CUDA
- GPU-accelerated computation and interactive display of molecular orbitals
- Temporal data mining for neuroscience
- GPU -based parallelization for fast circuit optimization
- Fast graph cuts for computer vision
- Real-time stereo on GPGPU using progressive multi-resolution adaptive windows
- GPU image demosaicing
- Tomographic image reconstruction from unordered lines with CUDA
- Medical image processing using GPU -accelerated ITK image filters
- 41 more chapters of innovative GPU computing ideas, written to be accessible to researchers from any domain
GPU Computing Gems: Emerald Edition is the first volume in Morgan Kaufmann's Applications of GPU Computing Series, offering the latest insights and research in computer vision, electronic design automation, emerging data-intensive applications, life sciences, medical imaging, ray tracing and rendering, scientific simulation, signal and audio processing, statistical modeling, and video / image processing.
- Covers the breadth of industry from scientific simulation and electronic design automation to audio / video processing, medical imaging, computer vision, and more
- Many examples leverage NVIDIA's CUDA parallel computing architecture, the most widely-adopted massively parallel programming solution
- Offers insights and ideas as well as practical "hands-on" skills you can immediately put to use