By Wen-mei W. Hwu
"...the excellent better half to Programming vastly Parallel Processors by means of Hwu & Kirk." -Nicolas Pinto, learn Scientist at Harvard & MIT, NVIDIA Fellow 2009-2010
Graphics processing devices (GPUs) can do even more than render pix. Scientists and researchers more and more glance to GPUs to enhance the potency and function of computationally-intensive experiments throughout various disciplines.
GPU Computing gem stones: Emerald Edition brings their recommendations to you, showcasing GPU-based recommendations including:
* Black gap simulations with CUDA
* GPU-accelerated computation and interactive exhibit of molecular orbitals
* Temporal information mining for neuroscience
* GPU -based parallelization for quick circuit optimization
* quick graph cuts for desktop vision
* Real-time stereo on GPGPU utilizing innovative multi-resolution adaptive windows
* GPU photograph demosaicing
* Tomographic picture reconstruction from unordered traces with CUDA
* scientific snapshot processing utilizing GPU -accelerated ITK snapshot filters
* 41 extra chapters of leading edge GPU computing principles, written to be available to researchers from any domain
GPU Computing gem stones: Emerald Edition is the 1st quantity in Morgan Kaufmann's Applications of GPU Computing Series, providing the newest insights and learn in desktop imaginative and prescient, digital layout automation, rising data-intensive functions, lifestyles sciences, scientific imaging, ray tracing and rendering, clinical simulation, sign and audio processing, statistical modeling, and video / picture processing.
* Covers the breadth of from clinical simulation and digital layout automation to audio / video processing, clinical imaging, desktop imaginative and prescient, and more
* Many examples leverage NVIDIA's CUDA parallel computing structure, the main widely-adopted vastly parallel programming solution
* deals insights and concepts in addition to useful "hands-on" abilities you could instantly placed to use
Read or Download GPU Computing Gems, Emerald Edition (Applications of GPU Computing Series) PDF
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Extra resources for GPU Computing Gems, Emerald Edition (Applications of GPU Computing Series)
We present an algorithmic redesign allowing GPU implementation of such a low arithmetic-intensity kernel and discuss techniques for memory optimization that enable large speedup. org/home/siml under a BSD license. 1 INTRODUCTION, PROBLEM STATEMENT, AND CONTEXT Chemical informatics uses computational methods to analyze chemical datasets for applications that include search and classification of known chemicals, virtually screening digital libraries of chemicals to find ones that may be active as potential drugs and predicting and optimizing the properties of existing active compounds.
LINGO is a string similarity algorithm that, in its canonical CPU implementation, is bandwidth intensive and branch heavy, with limited data parallelism. We present an algorithmic redesign allowing GPU implementation of such a low arithmetic-intensity kernel and discuss techniques for memory optimization that enable large speedup. org/home/siml under a BSD license. 1 INTRODUCTION, PROBLEM STATEMENT, AND CONTEXT Chemical informatics uses computational methods to analyze chemical datasets for applications that include search and classification of known chemicals, virtually screening digital libraries of chemicals to find ones that may be active as potential drugs and predicting and optimizing the properties of existing active compounds.
PAPER uses blocks of 64 threads to maximize the number of registers available to each thread. While it can be advantageous in some cases to use larger thread blocks to hide memory latency, in our application we typically have multiple thread blocks available on each multiprocessor. Since scheduling is done on a per-warp basis, using many smaller thread blocks is sufficient. In typical use cases, the number of terms to be calculated in the objective is larger than the number of available threads: typical molecules are 20-40 atoms, so that normal calculations will have 400-1600 terms.