Scalable Parallel Programming with CUDA - ACM Queue
Since NVIDIA released CUDA in 2007, developers have rapidly developed scalable parallel programs for a wide range of applications, including computational chemistry, sparse matrix solvers, sorting, searching, and physics models. These applications scale transparently to hundreds of processor cores and thousands of concurrent threads.
Abstract/Bio - Stanford University
John Nickolls is director of architecture at NVIDIA for GPU computing. He was previously with Broadcom, Silicon Spice, Sun Microsystems, and was a co-founder of MasPar Computer. His interests include parallel processing systems, languages, and architectures.
Scalable Parallel Programming with CUDA: Is CUDA the parallel ...
2008年3月1日 · Abstract. The advent of multicore CPUs and manycore GPUs means that mainstream processor chips are now parallel systems. Furthermore, their parallelism continues to scale with Moore’s law. The challenge is to develop mainstream application software that transparently scales its parallelism to leverage the increasing number of processor cores ...
2008年2月27日 · CUDA parallel programming model introduced in 2007. Write C code for one thread Instantiate parallel thread blocks Tens of thousands of CUDA developers 50M. NVIDIA ships 1M CUDA-capable GPUs a week. Over 50 M CUDA-capable GPUs shipped 25M. Unique opportunity to innovate and develop widely-deployed parallel applications. 2006. 2007.
[PDF] Scalable parallel programming - Semantic Scholar
Parallel Computing Experiences with Cuda the Cuda Programming Model Provides a Straightforward Means of Describing Inherently Parallel Computations, and Nvidia's Tesla Gpu Architecture Delivers High Computational Throughput on Massively Parallel Problems.
CUDA applications perform well on Tesla-architecture GPUs because CUDA’s parallelism, synchronization, shared memories, and hierarchy of thread groups map efficiently to features of the GPU architecture, and because CUDA expresses application parallelism well. REFERENCES 1. Lindholm, E., Nickolls, J., Oberman, S., Montrym, J. 2008.
Scalable Parallel Programming with CUDA: Is CUDA the parallel ...
2008年2月29日 · TL;DR: In this paper, the performance of non-graphics applications written in NVIDIA's CUDA programming model is evaluated on a microarchitecture performance simulator that runs NVIDIA's parallel thread execution (PTX) virtual instruction set.
(PDF) Scalable parallel programming with CUDA (2008) | John R. Nickolls …
The advent of multicore CPUs and manycore GPUs means that mainstream processor chips are now parallel systems. Furthermore, their parallelism continues to scale with Moore's law. The challenge is to develop mainstream application software that transparently scales its parallelism to leverage the increasing number of processor cores, much as 3D graphics applications transparently scale their ...
Scalable Parallel Programming with CUDA | Research - NVIDIA
2008年3月1日 · Scalable Parallel Programming with CUDA. The advent of multicore CPUs and manycore GPUs means that mainstream processor chips are now parallel systems. Furthermore, their parallelism continues to scale with Moore’s law. The challenge is to develop mainstream application software that transparently scales its parallelism to leverage the ...
Parallel Computing Experiences with CUDA - IEEE Xplore
2008年9月19日 · Abstract: The CUDA programming model provides a straightforward means of describing inherently parallel computations, and NVIDIA's Tesla GPU architecture delivers high computational throughput on massively parallel problems. This article surveys experiences gained in applying CUDA to a diverse set of problems and the parallel speedups over ...