high performance computing on graphics processing units: hgpu.org

Jiajun Huang, Sheng Di, Xiaodong Yu, Yujia Zhai, Jinyang Liu, Yafan Huang, Ken Raffenetti, Hui Zhou, Kai Zhao, Zizhong Chen, Franck Cappello, Yanfei Guo, Rajeev Thakur

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Tags: Compression, Computer science, GPU cluster, MPI, nVidia, nVidia A100

August 13, 2023 by hgpu

A Model Extraction Attack on Deep Neural Networks Running on GPUs

Jonah G. O'Brien Weiss

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Tags: Computer science, Neural networks, nVidia, nVidia Quadro RTX 8000, Security, Tesla T4

August 13, 2023 by hgpu

SYnergy: Fine-grained Energy-Efficient Heterogeneous Computing for Scalable Energy Saving

Kaijie Fan, Marco D'Antonio, Lorenzo Carpentieri, Biagio Cosenza, Federico Ficarelli, Daniele Cesarini

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, Energy-efficient computing, GPU cluster, Heterogeneous systems, Machine learning, nVidia, nVidia V100, SYCL

August 13, 2023 by hgpu

Static and Dynamic Analyses for Efficient GPU Execution

Philip Munksgaard

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, nVidia, nVidia A100, OpenCL, Performance, Thesis

August 13, 2023 by hgpu

Isolated Scheduling for Distributed Training Tasks in GPU Clusters

Xinchi Han, Weihao Jiang, Peirui Cao, Qinwei Yang, Yunzhuo Liu, Shuyao Qi, Shengkai Lin, Shizhen Zhao

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Tags: Computer science, GPU cluster, Machine learning, Neural networks, nVidia, nVidia V100, Package

August 13, 2023 by hgpu

Monadic Deep Learning

Bo Yang, Zhihao Zhang Kirisame Marisa, Kai Shi

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Tags: Computer science, CUDA, Deep learning, Java, Neural networks, OpenCL, Package, Scala

July 30, 2023 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

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high performance computing on graphics processing units: hgpu.org

Applications

Novel insights on atomic synchronization for sort-based group-by on GPUs

Sieve: Stratified GPU-Compute Workload Sampling

Porting Batched Iterative Solvers onto Intel GPUs with SYCL

Increased reliability on Intel GPUs via software diverse redundancy

Quantifying OpenMP: Statistical Insights into Usage and Adoption

Generating Parallel OpenCL and OpenMP Programs from Dataflow Graphs

gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters

A Model Extraction Attack on Deep Neural Networks Running on GPUs

SYnergy: Fine-grained Energy-Efficient Heterogeneous Computing for Scalable Energy Saving

Static and Dynamic Analyses for Efficient GPU Execution

Isolated Scheduling for Distributed Training Tasks in GPU Clusters

Monadic Deep Learning

Recent source codes

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Most viewed papers (last 30 days)