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FlexGrip: A Soft GPGPU for FPGAs

Kevin Andryc, Murtaza Merchant, Russell Tessier

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Tags: Computer science, CUDA, FPGA, nVidia

October 19, 2013 by hgpu

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Niklas Karlsson

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Tags: Algorithms, CUDA, Fluid dynamics, Laplace and Poisson equation, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 660 Ti, Poisson equation, Thesis

October 19, 2013 by hgpu

Massively Parallel Jacobian Computation

Wanqi Li

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Tags: CUDA, Mathematics, nVidia, nVidia GeForce GT 650 M, Package, Thesis

October 19, 2013 by hgpu

Efficient fine grained shared buffer management for multiple OpenCL devices

Chang-qing Xun, Dong Chen, Qiang Lan, Chun-yuan Zhang

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Tags: Computer science, Heterogeneous systems, Memory model, nVidia, OpenCL, Tesla C2050

October 19, 2013 by hgpu

Construction of a Virtual Cluster by Integrating PCI Pass-Through for GPU and InfiniBand Virtualization in Cloud

Chao-Tung Yang, Wei-Shen Ou

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Tags: Cloud, Cluster computing, Computer science, CUDA, GPU cluster, nVidia, Tesla C2050, Tesla C2070, Tesla C2075, Tesla K20, Virtualization

October 19, 2013 by hgpu

Early Experiences in Running Many-Task Computing Workloads on GPGPUs

Scott J. Krieder, Benjamin Grimmer, Ioan Raicu

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Tags: Computer science, CUDA, nVidia, Task scheduling

October 19, 2013 by hgpu

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Carlos Roberto Valencio, Guilherme Priolli Daniel, Camila Alves de Medeiros, Adriano Mauro Cansian

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GT 525 M

October 18, 2013 by hgpu

Progressive Photon Mapping on GPUs

Stian Aaraas Pedersen

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Overview, Package, Raytracing, Rendering, Thesis

October 18, 2013 by hgpu

OpenACC-based Snow Simulation

Magnus Alvestad Mikalsen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Performance, Tesla C2070, Tesla K20, Thesis

October 18, 2013 by hgpu

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Federico Ciccozzi

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, nVidia

October 18, 2013 by hgpu

Heterogeneous FTDT for Seismic Processing

Andreas Berg Skomedal

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Tags: CUDA, Earth and Space Sciences, FDTD, Finite-difference time-domain, Geoscience, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Package, Seismology, Tesla K20, Thesis

October 18, 2013 by hgpu

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Jing Jin, Xianggao Cai, Xiaola Lin

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Tesla C2050

October 18, 2013 by hgpu

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

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

FlexGrip: A Soft GPGPU for FPGAs

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Massively Parallel Jacobian Computation

Efficient fine grained shared buffer management for multiple OpenCL devices

Early Experiences in Running Many-Task Computing Workloads on GPGPUs

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Progressive Photon Mapping on GPUs

OpenACC-based Snow Simulation

Towards Code Generation from Design Models for Embedded Systems on Heterogeneous CPU-GPU Platforms

Heterogeneous FTDT for Seismic Processing

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Recent source codes

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

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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