high performance computing on graphics processing units: hgpu.org

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Productivity, Portability, Performance: Data-Centric Python

Alexandros Nikolaos Ziogas, Timo Schneider, Tal Ben-Nun, Alexandru Calotoiu, Tiziano De Matteis, Johannes de Fine Licht, Luca Lavarini, Torsten Hoefler

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Tags: Computer science, FPGA, HPC, nVidia, Python, Tesla V100

July 4, 2021 by hgpu

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis

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Tags: Bayesian, Computer science, CUDA, Deep learning, FPGA, HPC, Machine learning, MPI, nVidia, OpenMPI, Package, Tesla A100, Tesla V100

June 20, 2021 by hgpu

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

Keichi Takahashi, Wassapon Watanakeesuntorn, Kohei Ichikawa, Joseph Park, Ryousei Takano, Jason Haga, George Sugihara, Gerald M. Pao

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Tags: Computer science, CUDA, HPC, nVidia, OpenCL, Package, Performance, performance portability

May 30, 2021 by hgpu

Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

Manuel Costanzo, Enzo Rucci, Ulises Costi, Franco Chichizola, Marcelo Naiouf

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Tags: Algorithms, All-Pairs Distance, Computer science, CUDA, HPC, Intel, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan X, Package

May 23, 2021 by hgpu

NPBench: A Benchmarking Suite for High-Performance NumPy

Alexandros Nikolaos Ziogas, Tal Ben-Nun, Timo Schneider, Torsten Hoefler

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Tags: Benchmarking, Computer science, CUDA, HPC, Linear Algebra, nVidia, Package, Performance, Python, Tesla V100

May 16, 2021 by hgpu

GPGPU Task Scheduling Technique for Reducing the Performance Deviation of Multiple GPGPU Tasks in RPC-Based GPU Virtualization Environments

Jihun Kang, Heonchang Yu

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Tags: AMD Radeon RX 570, ATI, Cloud, Computer science, HPC, OpenCL, Task scheduling, Virtualization

March 21, 2021 by hgpu

Using hardware performance counters to speed up autotuning convergence on GPUs

Jiří Filipovič, Jana Hozzová, Amin Nezarat, Jaroslav Oľha, Filip Petrovič

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Tags: Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2080, OpenCL, Package, Performance, Vulkan

February 23, 2021 by hgpu

triSYCL for Xilinx FPGA

Andrew Gozillon, Ronan Keryell, Lin-Ya Yu, Gauthier Harnisch, Paul Keir

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Tags: Computer science, FPGA, HPC, LLVM, Package, SYCL

February 7, 2021 by hgpu

Instruments of Productivity for High Performance Computing

Olivier Aumage

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Tags: Computer science, HPC, Thesis

January 17, 2021 by hgpu

Hardware Acceleration of HPC Computational Flow Dynamics using HBM-enabled FPGAs

Tom Hogervorst, Tong Dong Qiu, Giacomo Marchiori, Alf Birger, Markus Blatt, Razvan Nane

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Tags: Computer science, CUDA, FPGA, Hardware Architecture, HPC, OpenCL, Sparse

January 10, 2021 by hgpu

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Xuewen Cui

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Tags: Artificial intelligence, Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, OpenMP, Performance, Tesla K40, Tesla P100, Tesla V100, Thesis

December 20, 2020 by hgpu

Python Workflows on HPC Systems

Dominik Strassel, Philipp Reusch, Janis Keuper

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Tags: Computer science, CUDA, Deep learning, GPU cluster, HPC, Machine learning, nVidia, PC cluster, Python

December 6, 2020 by hgpu

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

Automated Instruction Encoding Synthesis for Modern GPU ISA Compression

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Productivity, Portability, Performance: Data-Centric Python

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

kEDM: A Performance-portable Implementation of Empirical Dynamic Modeling using Kokkos

Comparison of HPC Architectures for Computing All-Pairs Shortest Paths. Intel Xeon Phi KNL vs NVIDIA Pascal

NPBench: A Benchmarking Suite for High-Performance NumPy

Using hardware performance counters to speed up autotuning convergence on GPUs

triSYCL for Xilinx FPGA

Instruments of Productivity for High Performance Computing

Hardware Acceleration of HPC Computational Flow Dynamics using HBM-enabled FPGAs

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Python Workflows on HPC Systems

Recent source codes

AutoTuneBench: Trustworthy Measurement for Agent Auto-Tuning of LLM Serving Engines

nvsass-disassembler

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

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

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