high performance computing on graphics processing units: hgpu.org

Ka Hei Martin Kwok, Matti Kortelainen, Giuseppe Cerati, Alexei Strelchenko, Oliver Gutsche, Allison Reinsvold Hall, Steve Lantz, Michael Reid, Daniel Riley, Sophie Berkman, Seyong Lee, Hammad Ather, Boyana Norris, Cong Wang

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Tags: AMD Radeon Instinct MI100, ATI, HEP, Intel, Intel Arc A770, nVidia, nVidia A100, nVidia V100, OpenMP, performance portability, Physics, SYCL

January 28, 2024 by hgpu

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

Qian Gong, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, Anand Rangarajan, Lipeng Wan, Nicolas Vidal, Qing Liu, Ana Gainaru, Norbert Podhorszki, Richard Archibald, Sanjay Ranka, Scott Klasky

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Tags: Compression, Computer science, CUDA, HIP, HPC, Numerical Analysis, nVidia, nVidia V100, OpenMP, Package, SYCL

January 21, 2024 by hgpu

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Shiwei Zhang, Lansong Diao, Chuan Wu, Zongyan Cao, Siyu Wang, Wei Lin

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Tags: Computer science, CUDA, Deep learning, Distributed computing, GPU cluster, nVidia, nVidia A100, nVidia P100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Foteini Strati, Xianzhe Ma, Ana Klimovic

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia A100, nVidia V100, Package, PyTorch

January 14, 2024 by hgpu

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

Aristotle Martin, Geng Liu, William Ladd, Seyong Lee, John Gounley, Jeffrey Vetter, Saumil Patel, Silvio Rizzi, Victor Mateevitsi, Joseph Insley, Amanda Randles

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, CUDA, Fluid dynamics, Heterogeneous systems, HIP, nVidia, nVidia A100, nVidia V100, performance portability, SYCL

December 31, 2023 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

FTTN: Feature-Targeted Testing for Numerical Properties of NVIDIA & AMD Matrix Accelerators

Assessing opportunities of SYCL for biological sequence alignment on GPU-based systems

TransAxx: Efficient Transformers with Approximate Computing

An Evaluative Comparison of Performance Portability across GPU Programming Models

Application of performance portability solutions for GPUs and many-core CPUs to track reconstruction kernels

MGARD: A multigrid framework for high-performance, error-controlled data compression and refactoring

HAP: SPMD DNN Training on Heterogeneous GPU Clusters with Automated Program Synthesis

Orion: Interference-aware, Fine-grained GPU Sharing for ML Applications

Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations

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