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GPU-accelerated Bernstein-Bezier discontinuous Galerkin methods for wave problems

Jesse Chan, T. Warburton

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Tags: Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 980, OCCA

December 22, 2015 by hgpu

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Feng Yuan, Tang Xiaobin, Gong Xiaoyan

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Tags: Computer science, Electrodynamics, FDTD, Finite-difference time-domain, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Physics, Tesla K20, Tesla M2070

December 22, 2015 by hgpu

Performance and Productivity of Parallel Python Programming: A study with a CFD Test Case

Achim Basermann, Melven Rohrig-Zollner, Joachim Illmer

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Tags: CUDA, Fluid dynamics, Fortran, nVidia, Performance, Python, Tesla C2075

December 22, 2015 by hgpu

A time-energy performance analysis of MapReduce on heterogeneous systems with GPUs

Dumitrel Loghin, Lavanya Ramapantulu, Oana Barbu, Yong Meng Teo

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, nVidia GeForce GTX 750 Ti, nVidia Jetson TK1

December 22, 2015 by hgpu

Autotuning Stencils Codes with Algorithmic Skeletons

Chris Cummins

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 590, nVidia GeForce GTX 690, nVidia GeForce GTX Titan, OpenCL, Package

December 19, 2015 by hgpu

Study, Modelling and Implementation of the Level Set Method Used in Micromachining Processes

Carles Montoliu Alvaro

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 560, nVidia GeForce GTX Titan, Thesis

December 19, 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

Efficient Query Processing in Co-Processor-accelerated Databases

Sebastian Bress

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Package, Tesla C1060, Tesla C2050, Thesis

December 19, 2015 by hgpu

Bigger Buffer k-d Trees on Multi-Many-Core Systems

Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes

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Tags: Computer science, KD-tree, Nearest neighbour, nVidia, nVidia GeForce GTX Titan Z, OpenCL, Package

December 15, 2015 by hgpu

A CUDA Kernel Scheduler Exploiting Static Data Dependencies

Eva Burrows

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Tags: Computer science, CUDA, nVidia, Task scheduler

December 15, 2015 by hgpu

Run-time support for multi-level disjoint memory address spaces

Javier Bueno Hedo

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Tags: Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, OmpSs, OpenMP, Thesis

December 15, 2015 by hgpu

Compressed Dynamic Mode Decomposition for Real-Time Object Detection

N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 950 M, Sensing

December 15, 2015 by hgpu

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

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

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-accelerated Bernstein-Bezier discontinuous Galerkin methods for wave problems

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Performance and Productivity of Parallel Python Programming: A study with a CFD Test Case

A time-energy performance analysis of MapReduce on heterogeneous systems with GPUs

Autotuning Stencils Codes with Algorithmic Skeletons

Study, Modelling and Implementation of the Level Set Method Used in Micromachining Processes

Challenges Adapting CUDA PIC Codes to multiple GPUs

Efficient Query Processing in Co-Processor-accelerated Databases

Bigger Buffer k-d Trees on Multi-Many-Core Systems

A CUDA Kernel Scheduler Exploiting Static Data Dependencies

Run-time support for multi-level disjoint memory address spaces

Compressed Dynamic Mode Decomposition for Real-Time Object Detection

Recent source codes

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

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

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

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