high performance computing on graphics processing units: hgpu.org

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Predicting the Execution Time of a kernel on a specific GPU using PTX code

Monika Dagar, Jorge Roldan

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX 1650, nVidia GeForce GTX Titan XP, Performance, PTX, Tesla K20, Tesla K80, Tesla M60, Tesla P100, Tesla T4, Tesla V100

October 22, 2023 by hgpu

Advanced Joins on GPUs

Christos Bellas

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

March 27, 2022 by hgpu

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan XP, Package, Performance, Tesla P100, Tesla V100

January 23, 2022 by hgpu

GCN Inference Acceleration using High-Level Synthesis

Yi Chien Lin, Bingyi Zhang, Viktor Prasanna

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Tags: Computer science, Data parallelism, Design space exploration, FPGA, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package

October 10, 2021 by hgpu

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Tadeusz Tomczak

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Tags: cfd, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX Titan XP, Package

September 5, 2021 by hgpu

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Biagio Cosenza, Nikita Popov, Ben Juurlink, Paul Richmond, Mozhgan Kabiri Chimeh, Carmine Spagnuolo, Gennaro Cordasco, Vittorio Scarano

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Tags: Compilers, Computer science, CUDA, DSL, nVidia, nVidia GeForce GTX Titan XP, Package

January 24, 2021 by hgpu

Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer

Suyoung Lee, HyungSeok Han, Sang Kil Cha, Sooel Son

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Tags: Computer science, Java, Neural networks, nVidia, nVidia GeForce GTX Titan XP, Package, Python, PyTorch, Security

August 30, 2020 by hgpu

Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs

Xueying Wang, Guangli Li, Xiao Dong, Jiansong Li, Lei Liu, Xiaobing Feng

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce GTX Titan XP, Tesla P4

July 19, 2020 by hgpu

Fast Gunrock Subgraph Matching (GSM) on GPUs

Leyuan Wang, John D. Owens

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Tags: Computer science, Graph theory, nVidia, nVidia GeForce GTX Titan V, nVidia GeForce GTX Titan XP, Package

March 8, 2020 by hgpu

Porting tree-based hash table compression to GPGPU model checking

Danny Bergsma

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Tags: Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

December 29, 2019 by hgpu

Performance Impact of Memory Channels on Sparse and Irregular Algorithms

Oded Green, James Fox, Jeffrey Young, Jun Shirako, David Bader

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce GTX Titan XP, Performance, Sparse, Tesla P100, Tesla V100

October 13, 2019 by hgpu

Memory-Efficient Object-Oriented Programming on GPUs

Matthias Springer

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 940 M, nVidia GeForce GTX 980, nVidia GeForce GTX Titan XP, Package, Programming Languages, Thesis

August 25, 2019 by hgpu

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

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

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

Efficient GPU Implementation of Multi-Precision Integer Division

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

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

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

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high performance computing on graphics processing units: hgpu.org

Predicting the Execution Time of a kernel on a specific GPU using PTX code

Advanced Joins on GPUs

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

GCN Inference Acceleration using High-Level Synthesis

Data-Oriented Language Implementation of Lattice-Boltzmann Method for Dense and Sparse Geometries

Easy and Efficient Agent-based Simulations with the OpenABL Language and Compiler

Montage: A Neural Network Language Model-Guided JavaScript Engine Fuzzer

Accelerating Deep Learning Inference with Cross-Layer Data Reuse on GPUs

Fast Gunrock Subgraph Matching (GSM) on GPUs

Porting tree-based hash table compression to GPGPU model checking

Performance Impact of Memory Channels on Sparse and Irregular Algorithms

Memory-Efficient Object-Oriented Programming on GPUs

Recent source codes

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

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

ParEval: A Parallel Code Evaluation Benchmark

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

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

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