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Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

Marius Erbert, Steffen Rechner, Matthias Muller-Hannemann

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Tags: Bioinformatics, Biology, Computer science, CUDA, nVidia, nVidia GeForce GTX 970, nVidia GeForce GTX Titan, Package

July 26, 2016 by hgpu

GPU-accelleration of image rendering and sorting algorithms with the OpenCL framework

Anders Soderholm, Justus Sorman

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Tags: Algorithms, Computer science, Heterogeneous systems, Image processing, Intel HD 4600, OpenCL, Rendering, Sorting, Thesis

July 26, 2016 by hgpu

Algorithmic Trading: A brief, computational finance case study on data centre FPGAs

Gordon Inggs

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Tags: AMD FirePro W5000, ATI, Computational finance, Computer science, Finance, FPGA, nVidia, nVidia Quadro K4000, OpenCL

July 20, 2016 by hgpu

Lowering IrGL to CUDA

Sreepathi Pai, Keshav Pingali

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Tags: Compilers, Computer science, CUDA, nVidia, Programming Languages

July 20, 2016 by hgpu

THOR: A New and Flexible Global Circulation Model to Explore Planetary Atmospheres

Joao M. Mendonca, Simon L. Grimm, Luc Grosheintz, Kevin Heng

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Tags: Astrophysics, CUDA, Earth and Planetary Astrophysics, Earth and Space Sciences, nVidia, Tesla K20

July 20, 2016 by hgpu

Scientific Computing Using Consumer Video-Gaming Hardware Devices

Glenn Volkema, Gaurav Khanna

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Tags: AMD Radeon R9 Fury X, ATI, Benchmarking, Computer science, nVidia, nVidia Tegra TX1, OpenCL, Package, Performance, Tesla K40

July 20, 2016 by hgpu

Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off

Hokchhay Tann, Soheil Hashemi, R. Iris Bahar, Sherief Reda

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Tags: Algorithms, ARM, ASIC, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia Tegra TX1

July 20, 2016 by hgpu

Accelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations

Hartwig Anzt, Marc Baboulin, Jack Dongarra, Yvan Fournier, Frank Hulsemann, Amal Khabou, Yushan Wang

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Tags: cfd, Conjugate gradient solver, CUDA, Fluid dynamics, nVidia, OpenCL, Tesla K40

July 18, 2016 by hgpu

IODA: an Input/Output Deep Architecture for image labeling

J. Lerouge, R. Herault, Clement Chatelain, F. Jardin, R. Modzelewski

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Python, Tesla C1060, Theano

July 18, 2016 by hgpu

HPC on the Intel Xeon Phi: Homomorphic Word Searching

Paulo Martins, Leonel Sousa

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Tags: Computer science, Intel Xeon Phi, Security

July 18, 2016 by hgpu

A Kinetic Vlasov Model for Plasma Simulation Using Discontinuous Galerkin Method on Many-Core Architectures

Noah Reddell

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Tags: OpenCL, Physics, Plasma physics, Thesis

July 18, 2016 by hgpu

Heterogeneous Computing for Data Stream Mining

Vladimir Petko

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Tags: Algorithms, Computer science, Data mining, Heterogeneous systems, Machine learning, Nearest neighbour, nVidia, OpenCL, Tesla C2050, Thesis

July 18, 2016 by hgpu

Agentic Code Optimization via Compiler-LLM Cooperation

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

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

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

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high performance computing on graphics processing units: hgpu.org

Applications

Gerbil: A Fast and Memory-Efficient k-mer Counter with GPU-Support

GPU-accelleration of image rendering and sorting algorithms with the OpenCL framework

Algorithmic Trading: A brief, computational finance case study on data centre FPGAs

Lowering IrGL to CUDA

THOR: A New and Flexible Global Circulation Model to Explore Planetary Atmospheres

Scientific Computing Using Consumer Video-Gaming Hardware Devices

Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off

Accelerating the Conjugate Gradient Algorithm with GPUs in CFD Simulations

IODA: an Input/Output Deep Architecture for image labeling

HPC on the Intel Xeon Phi: Homomorphic Word Searching

A Kinetic Vlasov Model for Plasma Simulation Using Discontinuous Galerkin Method on Many-Core Architectures

Heterogeneous Computing for Data Stream Mining

Recent source codes

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

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

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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