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10th PMBS@SC 2019: Denver, CO, USA
- 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, PMBS@SC 2019, Denver, CO, USA, November 18, 2019. IEEE 2019, ISBN 978-1-7281-5977-5
- Jan Laukemann, Julian Hammer, Georg Hager, Gerhard Wellein:
Automatic Throughput and Critical Path Analysis of x86 and ARM Assembly Kernels. 1-6 - Nan Ding, Samuel Williams:
An Instruction Roofline Model for GPUs. 7-18 - Justin Salmon, Simon McIntosh-Smith:
Exploiting Hardware-Accelerated Ray Tracing for Monte Carlo Particle Transport with OpenMC. 19-29 - Forrest Shriver, Seyong Lee, Steven Hamilton, Jeffrey S. Vetter, Justin Watson:
Enhancing Monte Carlo proxy applications on GPUs. 30-40 - Rahulkumar Gayatri, Kevin Gott, Jack Deslippe:
Comparing Managed Memory and ATS with and without Prefetching on NVIDIA Volta GPUs. 41-46 - Philip Taffet, Sanil Rao, Edgar A. León, Ian Karlin:
Testing the Limits of Tapered Fat Tree Networks. 47-52 - Ayaz Akram, Lina Sawalha:
Validation of the gem5 Simulator for x86 Architectures. 53-58 - Sudheer Chunduri, Elise Jennings, Kevin Harms, Christopher Knight, Scott Parker:
A Generalized Statistics-Based Model for Predicting Network-Induced Variability. 59-72 - Lorenz Braun, Holger Fröning:
CUDA Flux: A Lightweight Instruction Profiler for CUDA Applications. 73-81 - Karthik Vadambacheri Manian, Ching-Hsiang Chu, Ammar Ahmad Awan, Kawthar Shafie Khorassani, Hari Subramoni:
OMB-UM: Design, Implementation, and Evaluation of CUDA Unified Memory Aware MPI Benchmarks. 82-92 - Omar Aaziz, Courtenay Vaughan, Jonathan E. Cook, Jeanine E. Cook, Jeffery Kuehn, David Richards:
Fine-Grained Analysis of Communication Similarity between Real and Proxy Applications. 93-102 - Yihui Ren, Shinjae Yoo, Adolfy Hoisie:
Performance Analysis of Deep Learning Workloads on Leading-edge Systems. 103-113
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