high performance computing on graphics processing units: hgpu.org

Karthikeyan Vaidyanathan, Kiran Pamnany, Dhiraj D. Kalamkar, Alexander Heinecke, Mikhail Smelyanskiy, Jongsoo Park, Daehyun Kim, Aniruddha Shet G, Bharat Kaul, Balint Joo, Pradeep Dubey

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Tags: Cluster computing, Computer science, FFT, Intel Xeon Phi, Performance, QCD

August 15, 2014 by hgpu

Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures

Thomas R. W. Scogland, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Xeon Phi, nVidia, nVidia GeForce GTX 280, OpenCL, Performance, Tesla K20

August 15, 2014 by hgpu

Energy Evaluation for Applications with Different Thread Affinities on the Intel Xeon Phi

Gary Lawson, Masha Sosonkina, Yuzhong Shen

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Performance

August 15, 2014 by hgpu

GPU-SPARC: Accelerating Parallelism in Multi-GPU Real-Time Systems

Wookhyun Han, Hwidong Bae, Hyosu Kim, Jiyoen Lee, Insik Shin

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Tags: Computer science, nVidia, nVidia GeForce GTX 560 Ti, OpenCL, Package, Performance

August 13, 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

Performance analysis of a 240 thread tournament level MCTS Go program on the Intel Xeon Phi

Parallel Computation of Non-Bonded Interactions in Drug Discovery: Nvidia GPUs vs. Intel Xeon Phi

Performance Portability Study of Linear Algebra Kernels in OpenCL

Optimistic Parallelism on GPUs

Bandwidth Requirements of GPU Architectures

Estimating GPU Speedups for Programs Without Writing a Single Line of GPU Code

High Level Programming for Heterogeneous Architectures

Practical Symbolic Race Checking of GPU Programs

Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters

Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures

Energy Evaluation for Applications with Different Thread Affinities on the Intel Xeon Phi

GPU-SPARC: Accelerating Parallelism in Multi-GPU Real-Time Systems

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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