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GPU-Accelerated High-Level Synthesis for Bitwidth Optimization of FPGA Datapaths

Nachiket Kapre, Deheng Ye

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Tags: Benchmarking, Code generation, Computer science, CUDA, FPGA, nVidia, Package, Performance, Tesla K20

February 10, 2016 by hgpu

A Workload Balanced MapReduce Framework on GPU Platforms

Yue Zhang

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Tags: Benchmarking, Computer science, CUDA, MapReduce, nVidia, Performance, Tesla K40, Thesis

January 12, 2016 by hgpu

SqueezCL: Squeezing OpenCL Kernels for Approximate Computing on Contemporary GPUs

Atieh Lotf, Abbas Rahimi, Hadi Esmaeilzadeh, Rajesh K. Gupta

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Computer science, OpenCL

December 23, 2015 by hgpu

Challenges Adapting CUDA PIC Codes to multiple GPUs

Olav Emil Eiksund

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Tags: Benchmarking, CUDA, Electrostatics, FFT, nVidia, nVidia GeForce GTX 980, OpenMP, Particle simulation, Particle-in-cell methods, Physics, Plasma physics, Tesla K20, Thesis

December 19, 2015 by hgpu

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Code generation, Computer science, FPGA, OpenCL

December 12, 2015 by hgpu

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Anton Lokhmotov

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Tags: ARM, Benchmarking, Computer science, Linear Algebra, Mathematical Software, Matrix multiplication, OpenCL, Package, Performance

November 13, 2015 by hgpu

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

Hector Dearman

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Tags: Benchmarking, Computer science, CUDA, Differential equations, FEM, Finite element method, nVidia, nVidia GRID K520, OpenCL, Partial differential equations, PDEs, Thesis

November 3, 2015 by hgpu

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Linnan Wang, Wei Wu, Jianxiong Xiao, Yi Yang

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Tags: Benchmarking, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX Titan X, Package, Performance, Tesla K40

October 22, 2015 by hgpu

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Naohisa Hojo, Ittetsu Taniguchi, Hiroyuki Tomiyama

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Tags: Benchmarking, Computer science, OpenCL, Performance

October 16, 2015 by hgpu

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit

Felix Weninger, Johannes Bergmann, Bjorn Schuller

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Tags: Benchmarking, Computer science, CUDA, Neural networks, nVidia, nVidia GeForce GTX 560, Package, Speech recognition

October 8, 2015 by hgpu

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

Rahul Garg

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Tags: AMD Radeon HD 8650, ATI, ATI Radeon HD 7970, Benchmarking, Code generation, Computer science, Intel HD Graphics 4000, Matlab, Matrix multiplication, nVidia, nVidia GeForce GT 650 M, OpenCL, Package, Python, Tesla C2050, Thesis

October 6, 2015 by hgpu

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Shuoxin Lin

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Tags: Benchmarking, Computer science, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GTX 680, Thesis

September 29, 2015 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-Accelerated High-Level Synthesis for Bitwidth Optimization of FPGA Datapaths

A Workload Balanced MapReduce Framework on GPU Platforms

SqueezCL: Squeezing OpenCL Kernels for Approximate Computing on Contemporary GPUs

Challenges Adapting CUDA PIC Codes to multiple GPUs

GRATER: An Approximation Workflow for Exploiting Data-Level Parallelism in FPGA Acceleration

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Exploring Optimisations for the Local Assembly phase of Finite Element Methods on GPUs

BLASX: A High Performance Level-3 BLAS Library for Heterogeneous Multi-GPU Computing

Comparison of Thread Execution Methods for GPU-oriented OpenCL Programs on Multicore Processors

Introducing CURRENNT: The Munich Open-Source CUDA RecurREnt Neural Network Toolkit

A Toolkit for Building Dynamic Compilers for Array-Based Languages Targeting CPUs and GPUs

A Design Framework for Mapping Dataflow Graphs onto Heterogeneous Multiprocessor Platforms

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Agentic Code Optimization via Compiler-LLM Cooperation

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