The Experts below are selected from a list of 36 Experts worldwide ranked by ideXlab platform
Ying Zhang - One of the best experts on this subject based on the ideXlab platform.
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Comparability Graph coloring for optimizing utilization of stream register files in stream processors
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009Co-Authors: Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ZhangAbstract:A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all streams accessed must be communicated through the SRF (Stream Register File), a non-bypassing software-managed on-chip memory. Therefore, optimizing utilization of the SRF is crucial for good performance. The key insight is that the interference Graphs formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of multiple Comparability Graphs. We present a compiler algorithm that can find optimal or near-optimal colorings in stream IGs, thereby improving SRF utilization than the First-Fitbin-packing algorithm, the best in the literature.
Xuejun Yang - One of the best experts on this subject based on the ideXlab platform.
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Comparability Graph coloring for optimizing utilization of software managed stream register files for stream processors
ACM Transactions on Architecture and Code Optimization, 2012Co-Authors: Xuejun Yang, Li Wang, Jingling XueAbstract:The stream processors represent a promising alternative to traditional cache-based general-purpose processors in achieving high performance in stream applications (media and some scientific applications). In a stream programming model for stream processors, an application is decomposed into a sequence of kernels operating on streams of data. During the execution of a kernel on a stream processor, all streams accessed must be communicated through a nonbypassing software-managed on-chip memory, the SRF (Stream Register File). Optimizing utilization of the scarce on-chip memory is crucial for good performance. The key insight is that the interference Graphs (IGs) formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of Comparability Graphs. We present a compiler algorithm for finding optimal or near-optimal colorings, that is, SRF allocations in stream IGs, by computing a maximum spanning forest of the sub-IG formed by long live ranges, if necessary. Our experimental results validate the optimality and near-optimality of our algorithm by comparing it with an ILP solver, and show that our algorithm yields improved SRF utilization over the First-Fit bin-packing algorithm, the best in the literature.
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Comparability Graph coloring for optimizing utilization of stream register files in stream processors
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009Co-Authors: Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ZhangAbstract:A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all streams accessed must be communicated through the SRF (Stream Register File), a non-bypassing software-managed on-chip memory. Therefore, optimizing utilization of the SRF is crucial for good performance. The key insight is that the interference Graphs formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of multiple Comparability Graphs. We present a compiler algorithm that can find optimal or near-optimal colorings in stream IGs, thereby improving SRF utilization than the First-Fitbin-packing algorithm, the best in the literature.
Jingling Xue - One of the best experts on this subject based on the ideXlab platform.
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Comparability Graph coloring for optimizing utilization of software managed stream register files for stream processors
ACM Transactions on Architecture and Code Optimization, 2012Co-Authors: Xuejun Yang, Li Wang, Jingling XueAbstract:The stream processors represent a promising alternative to traditional cache-based general-purpose processors in achieving high performance in stream applications (media and some scientific applications). In a stream programming model for stream processors, an application is decomposed into a sequence of kernels operating on streams of data. During the execution of a kernel on a stream processor, all streams accessed must be communicated through a nonbypassing software-managed on-chip memory, the SRF (Stream Register File). Optimizing utilization of the scarce on-chip memory is crucial for good performance. The key insight is that the interference Graphs (IGs) formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of Comparability Graphs. We present a compiler algorithm for finding optimal or near-optimal colorings, that is, SRF allocations in stream IGs, by computing a maximum spanning forest of the sub-IG formed by long live ranges, if necessary. Our experimental results validate the optimality and near-optimality of our algorithm by comparing it with an ILP solver, and show that our algorithm yields improved SRF utilization over the First-Fit bin-packing algorithm, the best in the literature.
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Comparability Graph coloring for optimizing utilization of stream register files in stream processors
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009Co-Authors: Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ZhangAbstract:A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all streams accessed must be communicated through the SRF (Stream Register File), a non-bypassing software-managed on-chip memory. Therefore, optimizing utilization of the SRF is crucial for good performance. The key insight is that the interference Graphs formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of multiple Comparability Graphs. We present a compiler algorithm that can find optimal or near-optimal colorings in stream IGs, thereby improving SRF utilization than the First-Fitbin-packing algorithm, the best in the literature.
Li Wang - One of the best experts on this subject based on the ideXlab platform.
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Comparability Graph coloring for optimizing utilization of software managed stream register files for stream processors
ACM Transactions on Architecture and Code Optimization, 2012Co-Authors: Xuejun Yang, Li Wang, Jingling XueAbstract:The stream processors represent a promising alternative to traditional cache-based general-purpose processors in achieving high performance in stream applications (media and some scientific applications). In a stream programming model for stream processors, an application is decomposed into a sequence of kernels operating on streams of data. During the execution of a kernel on a stream processor, all streams accessed must be communicated through a nonbypassing software-managed on-chip memory, the SRF (Stream Register File). Optimizing utilization of the scarce on-chip memory is crucial for good performance. The key insight is that the interference Graphs (IGs) formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of Comparability Graphs. We present a compiler algorithm for finding optimal or near-optimal colorings, that is, SRF allocations in stream IGs, by computing a maximum spanning forest of the sub-IG formed by long live ranges, if necessary. Our experimental results validate the optimality and near-optimality of our algorithm by comparing it with an ILP solver, and show that our algorithm yields improved SRF utilization over the First-Fit bin-packing algorithm, the best in the literature.
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Comparability Graph coloring for optimizing utilization of stream register files in stream processors
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009Co-Authors: Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ZhangAbstract:A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all streams accessed must be communicated through the SRF (Stream Register File), a non-bypassing software-managed on-chip memory. Therefore, optimizing utilization of the SRF is crucial for good performance. The key insight is that the interference Graphs formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of multiple Comparability Graphs. We present a compiler algorithm that can find optimal or near-optimal colorings in stream IGs, thereby improving SRF utilization than the First-Fitbin-packing algorithm, the best in the literature.
Yu Deng - One of the best experts on this subject based on the ideXlab platform.
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Comparability Graph coloring for optimizing utilization of stream register files in stream processors
ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009Co-Authors: Xuejun Yang, Li Wang, Jingling Xue, Yu Deng, Ying ZhangAbstract:A stream processor executes an application that has been decomposed into a sequence of kernels that operate on streams of data elements. During the execution of a kernel, all streams accessed must be communicated through the SRF (Stream Register File), a non-bypassing software-managed on-chip memory. Therefore, optimizing utilization of the SRF is crucial for good performance. The key insight is that the interference Graphs formed by the streams in stream applications tend to be Comparability Graphs or decomposable into a set of multiple Comparability Graphs. We present a compiler algorithm that can find optimal or near-optimal colorings in stream IGs, thereby improving SRF utilization than the First-Fitbin-packing algorithm, the best in the literature.