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To exploit the benefits of throughput-optimized processors such as GPUs, applications need to be redesigned to achieve performance and efficiency. In this work, we present techniques to speed up statistical timing analysis on throughput processors. We draw upon advancements in improving the efficiency of Monte Carlo based statistical static timing analysis (MC SSTA) using techniques to reduce the...
The characteristics of modern graphics processing unit (GPU) is programmable, high price / performance ratio and high speed . It has a strong ability to adapt the parallel calculation, Based on this, the article study the general method of GPU calculating and use compute unified device architecture (CUDA) to design new parallel algorithm to accelerate the matrix inversion and binarization algorithm...
P systems or membrane systems provide a high level computational modeling framework that combines the structural and dynamic aspects of biological systems in a relevant and understandable way. P systems are massively parallel distributed, and non-deterministic systems. In this paper, we describe the implementation of a simulator for the class of recognizer P systems with active membranes by using...
We developed a complete GPU based data processing for cone-beam micro CT application which performs not only the reconstruction but also all the correction of the projection images on-the-fly. Test measurements were performed and processing times was compared on different hardware setups. The performance of the GPU together with our modified algorithm allow to process all the calculations within the...
Many applications in image processing have high inherent parallelism. FPGAs have shown very high performance in spite of their low operational frequency by fully extracting the parallelism. In recent micro processors, it also becomes possible to utilize the parallelism using multi-cores which support improved SIMD instructions, though programmers have to use them explicitly to achieve high performance...
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