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GPU-Accelerated Wire-Length Estimation for FPGA Placement FPGA放置的gpu加速线长估计
2011 Symposium on Application Accelerators in High-Performance Computing Pub Date : 2011-07-19 DOI: 10.1109/SAAHPC.2011.16
C. Fobel, G. Grewal, D. Stacey
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引用次数: 4
Transformation of Scientific Algorithms to Parallel Computing Code: Single GPU and MPI Multi GPU Backends with Subdomain Support 科学算法到并行计算代码的转换:支持子域的单GPU和MPI多GPU后端
2011 Symposium on Application Accelerators in High-Performance Computing Pub Date : 2011-07-01 DOI: 10.1109/SAAHPC.2011.12
B. Meyer, Christian Plessl, Jens Forstner
{"title":"Transformation of Scientific Algorithms to Parallel Computing Code: Single GPU and MPI Multi GPU Backends with Subdomain Support","authors":"B. Meyer, Christian Plessl, Jens Forstner","doi":"10.1109/SAAHPC.2011.12","DOIUrl":"https://doi.org/10.1109/SAAHPC.2011.12","url":null,"abstract":"We propose an approach for high-performance scientific computing that separates the description of algorithms from the generation of code for parallel hardware architectures like Multi-Core CPUs, GPUs or FPGAs. This way, a scientist can focus on his domain of expertise by describing his algorithms generically without the need to have knowledge of specific hardware architectures, programming languages, APIs or tool flows. We present our prototype implementation that allows for transforming generic descriptions of algorithms with intensive array-type data access to highly optimized code for GPU and multi GPU cluster systems. We evaluate the approach for an example from the domain of computational nanophotonics and show that our current tool flow is able to generate efficient code that achieves speedups of up to 15.3x for a single GPU and even 35.9x for a multi GPU setup compared to a reference CPU implementation.","PeriodicalId":331604,"journal":{"name":"2011 Symposium on Application Accelerators in High-Performance Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134395249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Efficient Implementation of the Overlap Operator on Multi-GPUs 多gpu上重叠算子的高效实现
2011 Symposium on Application Accelerators in High-Performance Computing Pub Date : 2011-06-24 DOI: 10.1109/SAAHPC.2011.13
A. Alexandru, M. Lujan, C. Pelissier, B. Gamari, F. Lee
{"title":"Efficient Implementation of the Overlap Operator on Multi-GPUs","authors":"A. Alexandru, M. Lujan, C. Pelissier, B. Gamari, F. Lee","doi":"10.1109/SAAHPC.2011.13","DOIUrl":"https://doi.org/10.1109/SAAHPC.2011.13","url":null,"abstract":"Lattice QCD calculations were one of the first applications to show the potential of GPUs in the area of high performance computing. Our interest is to find ways to effectively use GPUs for lattice calculations using the overlap operator. The large memory footprint of these codes requires the use of multiple GPUs in parallel. In this paper we show the methods we used to implement this operator efficiently. We run our codes both on a GPU cluster and a CPU cluster with similar interconnects. We find that to match performance the CPU cluster requires 20-30 times more CPU cores than GPUs.","PeriodicalId":331604,"journal":{"name":"2011 Symposium on Application Accelerators in High-Performance Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2011-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127410108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 30
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