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On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

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Tags: AMD FirePro S9150, ATI, Compilers, Computer science, CUDA, FPGA, nVidia, OpenCL, Package, performance portability, Tesla K80

July 14, 2019 by hgpu

GPU-based Parallel Computation Support for Stan

Rok Cesnovar, Steve Bronder, Davor Sluga, Jure Demsar, Tadej Ciglaric, Sean Talts, Erik Strumbelj

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Tags: AMD Radeon R9 Fury, ATI, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package, Tesla V100

July 10, 2019 by hgpu

PANNA: Properties from Artificial Neural Network Architectures

Ruggero Lot, Franco Pellegrini, Yusuf Shaidu, Emine Kucukbenli

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Tags: Deep learning, Machine learning, Molecular dynamics, Neural networks, Package, Physics, TensorFlow

July 10, 2019 by hgpu

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

Roberto Cavicchioli, Nicola Capodieci, Marco Solieri, Marko Bertogna

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Tags: Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Vulkan

July 7, 2019 by hgpu

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang

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Tags: ARM, CNN, Compilers, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia Jetson Nano, OpenCL, Package

July 7, 2019 by hgpu

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Axel Hübl

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Tags: CUDA, HPC, nVidia, Package, Particle-in-cell methods, Physics, Tesla P100, Thesis

July 4, 2019 by hgpu

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Huihui Sun, Florian Fey, Jie Zhao, Sergei Gorlatch

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Tags: Benchmarking, Code generation, Computer science, LLVM, OpenCL, Package, Performance

June 30, 2019 by hgpu

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Philippe Tillet, H. T. Kung, David Cox

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Tags: Compilers, Computer science, CUDA, Deep learning, High-level Languages, LLVM, Matrix multiplication, Neural networks, nVidia, nVidia GeForce GTX 1070, Package

June 30, 2019 by hgpu

HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling

Isabelly Rocha, Christian Göttel, Pascal Felber, Marcelo Pasin, Romain Rouvoy, Valerio Schiavoni

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Tags: ARM, Cloud, Computer science, FPGA, Heterogeneous systems, Package, Task scheduling

June 30, 2019 by hgpu

Heterogeneous Active Messages (HAM) – Implementing Lightweight Remote Procedure Calls in C++

Matthias Noack

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, Package

June 27, 2019 by hgpu

Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing

Bodun Hu, Christopher J. Rossbach

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Neural networks, nVidia, Package, Performance, Tesla P100

June 27, 2019 by hgpu

Data-Parallel Flattening by Expansion

Martin Elsman, Troels Henriksen, Niels Gustav Westphal Serup

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Tags: Code generation, Computer science, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package

June 23, 2019 by hgpu

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

A Performance Portable Matrix Free Dense MTTKRP in GenTen

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

Accelerating cosmological simulations on GPUs: a portable approach using OpenMP

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

ConCuR: Conciseness Makes State-of-the-Art Kernel Generation

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

VibeCodeHPC: An Agent-Based Iterative Prompting Auto-Tuner for HPC Code Generation Using LLMs

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

exa-AMD: An Exascale-Ready Framework for Accelerating the Discovery and Design of Functional Materials

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high performance computing on graphics processing units: hgpu.org

Applications

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

GPU-based Parallel Computation Support for Stan

PANNA: Properties from Artificial Neural Network Architectures

Novel Methodologies for Predictable CPU-To-GPU Command Offloading

A Unified Optimization Approach for CNN Model Inference on Integrated GPUs

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

WCCV: Improving the Vectorization of IF-statements with Warp-Coherent Conditions

Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations

Heterogeneous Active Messages (HAM) – Implementing Lightweight Remote Procedure Calls in C++

Mirovia: A Benchmarking Suite for Modern Heterogeneous Computing

Data-Parallel Flattening by Expansion

Recent source codes

Kernel Library for LLM Serving

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

Genten: Software for Generalized Tensor Decompositions by Sandia National Laboratories

Interleaved Learning and Exploration: A Self-Adaptive Fuzz Testing Framework for MLIR

Pinocchio: PINpointing Orbit Crossing Collapsed Hierarchical Objects

KernelCoder: trained on a curated dataset of reasoning traces and CUDA kernel pairs

VibeCodeHPC - Multi Agentic Vibe Coding for HPC

Compile-Time Resource Safety for GPU APIs: A Low-Overhead Typestate Framework

exa-AMD: Exascale Accelerated Materials Discovery

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