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Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Vivek K. Pallipuram

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, Performance, Tesla K20, Tesla M2075, Thesis

February 11, 2014 by hgpu

Auto-Generation and Auto-Tuning of 3D Stencil Codes on Homogeneous and Heterogeneous GPU Clusters

Yongpeng Zhang, Frank Mueller

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Optimization, Tesla C1060, Tesla C2050

February 5, 2014 by hgpu

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Angeles Navarro, Antonio Vilches, Francisco Corbera, Rafael Asenjo

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla S2050

February 4, 2014 by hgpu

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Farouk Mansouri, Sylvain Huet, Vincent Fristot, Dominique Houzet

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Tags: Computer science, CUDA, DSP, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia Quadro 4000, Signal processing

February 2, 2014 by hgpu

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

Xavier Lacoste, Mathieu Faverge, Pierre Ramet, Samuel Thibault, George Bosilca

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Sparse direct solvers, Tesla M2070

January 30, 2014 by hgpu

Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Gary Macindoe

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Heterogeneous systems, Linear Algebra, Machine learning, Matrix decomposition, nVidia, nVidia GeForce 9500 GT, nVidia GeForce GTX 285, Tesla S1070, Thesis

January 29, 2014 by hgpu

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

Jing Zhang, Hao Wang, Heshan Lin, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 7970, Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL, Task scheduling

January 29, 2014 by hgpu

On the Programmability and Performance of Heterogeneous Platforms

Konstantinos Krommydas, Thomas R.W. Scogland, Wu-chun Feng

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Tags: Computer science, CUDA, Heterogeneous systems, Intel Xeon Phi, N-body simulation, nVidia, OpenACC, Optimization, Tesla K20

January 29, 2014 by hgpu

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Ashis Kumar Dash

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Tags: Computer science, CUDA, Data parallelism, Heterogeneous systems, Matrix multiplication, nVidia, nVidia Quadro FX 3700

January 29, 2014 by hgpu

Scheduling on Manycore and Heterogeneous Graphics Processors

Stanley Tzeng

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 580, OpenCL, Thesis

January 28, 2014 by hgpu

gem5-gpu: A Heterogeneous CPU-GPU Simulator

Jason Power, Joel Hestness, Marc S. Orr, Mark D. Hill, David A. Wood

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Tags: Computer science, CUDA, GPGPU-sim, Heterogeneous systems, nVidia, nVidia GeForce GTX 580

January 26, 2014 by hgpu

On the Portability of the OpenCL Dwarfs on Fixed and Reconfigurable Parallel Platforms

Konstantinos Krommydas, Muhsen Owaida, Christos D. Antonopoulos, Nikolaos Bellas, Wu-chun Feng

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Tags: APU, ATI, ATI Radeon HD 7970, Computer science, FPGA, Heterogeneous systems, Intel Xeon Phi, OpenCL

January 23, 2014 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Exploring Multiple Levels of Performance Modeling for Heterogeneous Systems

Auto-Generation and Auto-Tuning of 3D Stencil Codes on Homogeneous and Heterogeneous GPU Clusters

Strategies for Maximizing Utilization in multi-CPU & multi-GPU Heterogeneous Architectures

Task migration of DSP application specified with a DFG and implemented with the BSP computing model on a CPU-GPU cluster

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

Hybrid algorithms for efficient Cholesky decomposition and matrix inverse using multicore CPUs with GPU accelerators

Consolidating Applications for Energy Efficiency in Heterogeneous Computing Systems

On the Programmability and Performance of Heterogeneous Platforms

A Performance Criteria for parallel Computation on basis of block size using CUDA Architecture

Scheduling on Manycore and Heterogeneous Graphics Processors

gem5-gpu: A Heterogeneous CPU-GPU Simulator

On the Portability of the OpenCL Dwarfs on Fixed and Reconfigurable Parallel Platforms

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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