منابع مشابه
CnC-CUDA: Declarative Programming for GPUs
The computer industry is at a major inflection point in its hardware roadmap due to the end of a decades-long trend of exponentially increasing clock frequencies. Instead, future computer systems are expected to be built using homogeneous and heterogeneous many-core processors with 10’s to 100’s of cores per chip, and complex hardware designs to address the challenges of concurrency, energy eff...
متن کاملA CUDA SIMT Interpreter for Genetic Programming
A Single Instruction Multiple Thread CUDA interpreter provides SIMD like parallel evaluation of the whole GP population of 1 4 million RPN expressions on graphics cards and nVidia Tesla T10P. Using sub-machine code GP a sustain peak performance of 212 billion GP operations per second (3300 speed up) and an average of 4.5 peta GP ops per day is reported for a single card on a Boolean induction b...
متن کاملDistributed Genetic Programming on GPUs using CUDA
Using of a cluster of Graphics Processing Unit (GPU) equipped computers, it is possible to accelerate the evaluation of individuals in Genetic Programming. Program compilation, fitness case data and fitness execution are spread over the cluster of computers, allowing for the efficient processing of very large datasets. Here, the implementation is demonstrated on datasets containing over 10 mill...
متن کاملCUDA-Lite: Reducing GPU Programming Complexity
Abstract. The computer industry has transitioned into multi-core and many-core parallel systems. The CUDA programming environment from NVIDIA is an attempt to make programming many-core GPUs more accessible to programmers. However, there are still many burdens placed upon the programmer to maximize performance when using CUDA. One such burden is dealing with the complex memory hierarchy. Effici...
متن کاملRealtime Dense Stereo Matching with Dynamic Programming in CUDA
Real-time depth extraction from stereo images is an important process in computer vision. This paper proposes a new implementation of the dynamic programming algorithm to calculate dense depth maps using the CUDA architecture achieving real-time performance with consumer graphics cards. We compare the running time of the algorithm against CPU implementation and demonstrate the scalability prope...
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ژورنال
عنوان ژورنال: The Journal of The Institute of Image Information and Television Engineers
سال: 2012
ISSN: 1342-6907,1881-6908
DOI: 10.3169/itej.66.813