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Programming Heterogeneous Systems from an Image Processing DSL

Jing Pu, Steven Bell, Xuan Yang, Jeff Setter, Stephen Richardson, Jonathan Ragan-Kelley, Mark Horowitz

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Tags: ARM, Computer science, Computer vision, CUDA, DSL, FPGA, Image processing, nVidia, nVidia Jetson TK1, OpenGL, Package

November 1, 2016 by hgpu

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Xiang Li, Tao Qin, Jian Yang, Tie-Yan Liu

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Tags: Algorithms, Computer science, Deep learning, Neural networks, NLP, nVidia, RNN, Tesla K20

November 1, 2016 by hgpu

Performance Optimization of 3-D Lattice Boltzmann Flow Solver on a GPU

Nhat-Phuong Tran, Myungho Lee, Sugwon Hong

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Tags: Computer science, CUDA, Fluid dynamics, Lattice Boltzmann model, Numerical simulation, nVidia, Performance, Tesla K20

November 1, 2016 by hgpu

Design and Analysis of Soft-Error Resilience Mechanisms for GPU Register File

Sparsh Mittal, Haonan Wang, Adwait Jog and Jeffrey Vetter

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Tags: GPU, Register file, Reliability

November 1, 2016 by sparsh0mittal

AQsort: Scalable Multi-Array In-Place Sorting with OpenMP

Daniel Langr, Pavel Tvrdik, Ivan Simecek

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Tags: Algorithms, Computer science, Intel Xeon Phi, OpenMP, Package, Sorting

October 29, 2016 by hgpu

Hetero-Mark, A Benchmark Suite for CPU-GPU Collaborative Computing

Yifan Sun, Xiang Gong, Amir Kavyan Ziabari, Leiming Yu, Xiangyu Li, Saoni Mukherjee, Carter McCardwell, Alejandro Villegas, David Kaeli

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Tags: Benchmarking, Computer science, Heterogeneous systems, OpenCL, Package, Performance

October 29, 2016 by hgpu

GPflow: A Gaussian process library using TensorFlow

Alexander G. de G. Matthews, Mark van der Wilk, Tom Nickson, Keisuke Fujii, Alexis Boukouvalas, Pablo Leon-Villagra, Zoubin Ghahramani, James Hensman

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce GTX Titan X, Package, Python, TensorFlow

October 29, 2016 by hgpu

GPU Performance Modeling and Optimization

Ang Li

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Performance, PTX, Thesis

October 29, 2016 by hgpu

GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

Yohei Miki, Masayuki Umemura

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Tags: Astrophysics, CUDA, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, nVidia GeForce GTX Titan X, Tesla K20, Tesla M2090

October 29, 2016 by hgpu

Accelerating BLAS on Custom Architecture through Algorithm-Architecture Co-design

Farhad Merchant, Tarun Vatwani, Anupam Chattopadhyay, Soumyendu Raha, S K Nandy, Ranjani Narayan

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Tags: Algorithms, BLAS, Computer science, CUDA, FPGA, Linear Algebra, Matrix multiplication, nVidia, Tesla C2050

October 29, 2016 by hgpu

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

Peter Sanders, Sebastian Lamm, Lorenz Hubschle-Schneider, Emanuel Schrade, Carsten Dachsbacher

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, Mathematical Software, nVidia, nVidia GeForce GTX 980 Ti, Package

October 22, 2016 by hgpu

Sparse-Matrix support for the SkePU library for portable CPU/GPU programming

Vishist Sharma

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Sparse matrix, Tesla M2050, Thesis

October 22, 2016 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

Applications

Programming Heterogeneous Systems from an Image Processing DSL

LightRNN: Memory and Computation-Efficient Recurrent Neural Networks

Performance Optimization of 3-D Lattice Boltzmann Flow Solver on a GPU

Design and Analysis of Soft-Error Resilience Mechanisms for GPU Register File

AQsort: Scalable Multi-Array In-Place Sorting with OpenMP

Hetero-Mark, A Benchmark Suite for CPU-GPU Collaborative Computing

GPflow: A Gaussian process library using TensorFlow

GPU Performance Modeling and Optimization

GOTHIC: Gravitational oct-tree code accelerated by hierarchical time step controlling

Accelerating BLAS on Custom Architecture through Algorithm-Architecture Co-design

Efficient Random Sampling – Parallel, Vectorized, Cache-Efficient, and Online

Sparse-Matrix support for the SkePU library for portable CPU/GPU programming

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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