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Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale

Dan Zhao, Siddharth Samsi, Joseph McDonald, Baolin Li, David Bestor, Michael Jones, Devesh Tiwari, Vijay Gadepally

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Tags: AI, Computer science, Energy-efficient computing, HPC, nVidia, nVidia A100

March 3, 2024 by hgpu

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Kade M. Heckel, Thomas Nowotny

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia RTX A6000, Package, Python

March 3, 2024 by hgpu

Parallel programming in mobile devices with FancyJCL

Sergio Afonso, Óscar Gómez-Cárdenes, Paula Expósito, Vicente Blanco, Francisco Almeida

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Tags: Computer science, DSP, Heterogeneous systems, Image processing, Java, OpenCL, Package

March 3, 2024 by hgpu

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

Sébastien Darche, Michel R. Dagenais

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, CUDA, HIP, nVidia, Package, Performance, Profiling

March 3, 2024 by hgpu

APPy: Annotated Parallelism for Python on GPUs

Tong Zhou, Jun Shirako, Vivek Sarkar

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Tags: Code generation, Compilers, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce RTX 3090, Python

February 25, 2024 by hgpu

Analyzing GPU Performance in Virtualized Environments: A Case Study

Adel Belkhiri, Michel Dagenais

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Tags: Computer science, CUDA, Java, nVidia, OpenCL, Package, Performance, Virtualization

February 25, 2024 by hgpu

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

Weile Luo, Ruibo Fan, Zeyu Li, Dayou Du, Qiang Wang, Xiaowen Chu

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia GeForce RTX 4090, nVidia H800, Performance, PTX

February 25, 2024 by hgpu

Green AI: A Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures

Negar Alizadeh, Fernando Castor

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Tags: Computer science, CUDA, Deep learning, Energy-efficient computing, nVidia, nVidia GeForce RTX 3070, Package, PyTorch, TensorFlow

February 25, 2024 by hgpu

TransAxx: Efficient Transformers with Approximate Computing

Dimitrios Danopoulos, Georgios Zervakis, Dimitrios Soudris, Jörg Henkel

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

February 18, 2024 by hgpu

Graphtoy: Fast Software Simulation of Applications for AMD’s AI Engines

Jonathan Strobl, Leonardo Solis-Vasquez, Yannick Lavan, Andreas Koch

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Tags: ATI, Computer science, FPGA, molecular docking, Package

February 18, 2024 by hgpu

An Evaluative Comparison of Performance Portability across GPU Programming Models

Joshua H. Davis, Pranav Sivaraman, Isaac Minn, Konstantinos Parasyris, Harshitha Menon, Giorgis Georgakoudis, Abhinav Bhatele

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct Mi50, ATI, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia V100, OpenACC, OpenMP, Performance, performance portability, SYCL

February 18, 2024 by hgpu

pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations

Ruben Laso, Diego Krupitza, Sascha Hunold

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Ampere A2, OpenMP, performance portability, Tesla P4

February 18, 2024 by hgpu

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

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high performance computing on graphics processing units: hgpu.org

Applications

Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale

Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networks

Parallel programming in mobile devices with FancyJCL

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

APPy: Annotated Parallelism for Python on GPUs

Analyzing GPU Performance in Virtualized Environments: A Case Study

Benchmarking and Dissecting the Nvidia Hopper GPU Architecture

Green AI: A Preliminary Empirical Study on Energy Consumption in DL Models Across Different Runtime Infrastructures

TransAxx: Efficient Transformers with Approximate Computing

Graphtoy: Fast Software Simulation of Applications for AMD’s AI Engines

An Evaluative Comparison of Performance Portability across GPU Programming Models

pSTL-Bench: A Micro-Benchmark Suite for Assessing Scalability of C++ Parallel STL Implementations

Recent source codes

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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