Results 291 to 300 of about 39,047 (336)

CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications

2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2019
GPUs are powerful, massively parallel processors, which require a vast amount of thread parallelism to keep their thousands of execution units busy, and to tolerate latency when accessing its high-throughput memory system. Understanding the behavior of massively threaded GPU programs can be difficult, even though recent GPUs provide an abundance of ...
Lorenz Braun, Holger Froning
openaire   +1 more source

An effective parallelization algorithm for DEM generalization based on CUDA

Environmental Modelling & Software, 2019
An effective parallelization algorithm based on the compute-unified-device-architecture (CUDA) is developed for DEM generalization that is critical to multi-scale terrain analysis.
Qianjiao Wu, Yumin Chen, John P. Wilson, Xuejun Liu, Huifang Li   +4 more
semanticscholar   +1 more source

Fast block distributed CUDA implementation of the Hungarian algorithm

J. Parallel Distributed Comput., 2019
The Hungarian algorithm solves the linear assignment problem in polynomial time. A GPU/CUDA implementation of this algorithm is proposed. GPUs are massive parallel machines.
P. Lopes, S. Yadav, Aleksandar Ilic, S. K. Patra   +3 more
semanticscholar   +1 more source

LICOM3-CUDA: a GPU version of LASG/IAP climate system ocean model version 3 based on CUDA

Journal of Supercomputing, 2023
Junlin Wei, Jinrong Jiang, Hailong Liu, Feng Zhang, P. Lin, Pengfei Wang, Yongqiang Yu, Xue-bin Chi, Lian Zhao, M. Ding, Yiwen Li, Zipeng Yu, Weipeng Zheng, Yuzhu Wang   +13 more
semanticscholar   +1 more source

Benchmarking OpenCL, OpenACC, OpenMP, and CUDA: programming productivity, performance, and energy consumption

ARMS-CC@PODC, 2017
Many modern parallel computing systems are heterogeneous at their node level. Such nodes may comprise general purpose CPUs and accelerators (such as, GPU, or Intel Xeon Phi) that provide high performance with suitable energy-consumption characteristics ...
Suejb Memeti, Lu Li, Sabri Pllana, J. Kolodziej, C. Kessler   +4 more
semanticscholar   +1 more source

Automating CUDA Synchronization via Program Transformation

International Conference on Automated Software Engineering, 2019
While CUDA has been the most popular parallel computing platform and programming model for general purpose GPU computing, CUDA synchronization undergoes significant challenges for GPU programmers due to its intricate parallel computing mechanism and ...
Mingyuan Wu, Lingming Zhang, Cong Liu, Shin Hwei Tan, Yuqun Zhang   +4 more
semanticscholar   +1 more source

???????????????????? ?????????????????? ????????????-???????????????? ?????? ????????????????????-???????????????????? ?????????????????? CUDA

2015
?????????????????? ???????????? ?????????????? ???????????????????? ?????????????????? ??????????????????????????????? ?????? ??????????????????-?????????????????? ?????????????????? CUDA. ???????????????? ???????????????????? ???????? ???????????? ?????????????????? ???? ?????????????????????????? ?? ???????????????????????? ?????????????????? ????????
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?????????? ???????????????????? ?????????????????? ???? ???????????????? ?????? ?????????????????????????? ????'?????????? ?? ?????????? ???? ?????????????????????? ?????????????????????? CUDA

2014
A search of arbitrary shape image fragments with full-search template matching on CUDA is examined. Different approaches to search area caching in a multiprocessor???s memory are proposed and analyzed. Acceleration on GPU in comparison to CPU is evaluated. The proposed algorithms can be used to accelerate object tracking in video.
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???????????? ?????????????????????????????????? ???????????????? ???? ???????????????? ?????????????????????????? FtsZ-??????????: ???????????????????? ???????????????????? cuda ?????? ?????????????????? ????????????????

2017
???????????????????? ?????????? ???? ???????????? ?????????????????????? ???????????????????????? ???????????????????? CUDA ?????? ?????????????????????? ?????????????????? ?? ???????????? ?????????????????????? ???????????????? ???? ????????????????????????????. ???? ???????????????? ???????????? ?? ?????????????????? Hex 6.1 ?????????????????? ???????
openaire   +1 more source

CUDA by Example: An Introduction to General-Purpose GPU Programming

Scalable Computing : Practice and Experience, 2010
Jie Cheng
semanticscholar   +1 more source