high performance computing on graphics processing units: hgpu.org

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Understanding the Costs of Many-Task Computing Workloads on Intel Xeon Phi Coprocessors

Jeffrey Johnson, Scott J. Krieder, Benjamin Grimmer, Justin M. Wozniaky, Michael Wildeyz, Ioan Raicu

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Tags: Computer science, Heterogeneous systems, Intel, Intel Phi

October 21, 2013 by hgpu

Optimization of the HEFT algorithm for a CPU-GPU environment

Karan R. Shetti, Suhaib A. Fahmy, Timo Bretschneider

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Tags: Algorithms, Computer science, Heterogeneous systems, Task scheduling

October 21, 2013 by hgpu

Energy Efficiency Studies of Mont Blanc Applications

Mads Holden

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Tags: ARM, Computer science, Energy-efficient computing, Matrix multiplication, OpenCL, Package, Thesis

October 21, 2013 by hgpu

Work Efficient Parallel Algorithms for Large Graph Exploration

Dip Sankar Banerjee, Shashank Sharma, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Graph theory, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

October 21, 2013 by hgpu

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

Sivaramakrishna Bharadwaj Indarapu, Manoj Maramreddy, Kishore Kothapalli

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, Sparse matrix

October 21, 2013 by hgpu

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

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

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

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

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

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high performance computing on graphics processing units: hgpu.org

Understanding the Costs of Many-Task Computing Workloads on Intel Xeon Phi Coprocessors

Optimization of the HEFT algorithm for a CPU-GPU environment

Energy Efficiency Studies of Mont Blanc Applications

Work Efficient Parallel Algorithms for Large Graph Exploration

Architecture-and Workload-Aware Heterogeneous Algorithms for Sparse Matrix Vector Multiplication

FlexGrip: A Soft GPGPU for FPGAs

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

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

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

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

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

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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