High Performance Computing Systems - Performance Modeling, Benchmarking and Simulation - Info and Reading Options

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Intro -- Preface -- Organization -- Contents -- Section A: Performance Benchmarking and Optimisation -- Algebraic Multigrid on a Dragonfly Network: First Experiences on a Cray XC30 -- 1 Introduction -- 2 Dragonfly Networks -- 2.1 Implementation on the Cray XC30 -- 2.2 Target System -- 3 Algebraic Multigrid -- 4 Performance Model -- 4.1 Model Specifics -- 4.2 Adaptation to Dragonfly Networks -- 5 Model Validation -- 5.1 Experimental Setup -- 5.2 Results -- 6 Model-Guided Performance Improvements -- 6.1 Approach -- 6.2 Redistribution Experiments -- 7 Conclusions -- References -- Performance Evaluation of Scientific Applications on POWER8 -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Hardware Counters -- 3.2 Performance Metrics -- 3.3 Porting and Tuning -- 4 Micro-benchmark Results -- 4.1 Instruction Throughput and Latency -- 4.2 Memory Sub-system (STREAM) -- 4.3 OpenMP Overheads -- 5 Application Performance Results -- 5.1 Lattice Boltzmann Performance Results -- 5.2 MAFIA Performance Results -- 5.3 NEST Performance Results -- 6 Summary and Conclusions -- References -- SPEC ACCEL: A Standard Application Suite for Measuring Hardware Accelerator Performance -- 1 Introduction -- 2 Related Work -- 3 Design and Principles of SPEC ACCEL -- 3.1 Benchmark Philosophy and General Design -- 3.2 Run Rules -- 4 Description of the Applications -- 4.1 SPEC ACCEL OCL Suite -- 4.2 SPEC ACCEL ACC Suite -- 5 Energy Awareness -- 6 Discussion of First Results -- 7 Summary and Future Work -- References -- A CUDA Implementation of the High Performance Conjugate Gradient Benchmark -- 1 Introduction -- 2 GPU Computing and CUDA -- 3 HPCG -- 3.1 The PCG Algorithm -- 3.2 Preconditioner -- 3.3 Selecting Node Count -- 4 CUDA Implementation -- 4.1 Baseline CUSPARSE -- 4.2 Reordering with Graph Coloring -- 4.3 Custom Kernels CSR Version -- 4.4 Optimized Version

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