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Thousand core chips: a technology perspective

Shekhar Borkar

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Tags: Architecture, Computer science, Review

January 7, 2011 by hgpu

A Unified Runtime System for Heterogeneous Multi-core Architectures

Cedric Augonnet, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, nVidia Quadro FX 4600

January 7, 2011 by hgpu

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Yonghong Yan, Max Grossman, Vivek Sarkar

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Tags: Computer science, CUDA, Java, nVidia, Package, Tesla C1060

January 7, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

Data transformations enabling loop vectorization on multithreaded data parallel architectures

Byunghyun Jang, Perhaad Mistry, Dana Schaa, Rodrigo Dominguez, David Kaeli

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Tags: ATI, ATI Radeon HD 3870, ATI Stream, Brook, Code generation, Compilers, Computer science, Optimization

January 7, 2011 by hgpu

Fast BVH Construction on GPUs

C. Lauterbach, M. Garland, S. Sengupta, D. Luebke, D. Manocha

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Tags: Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Raytracing

January 7, 2011 by hgpu

Low latency photon mapping using block hashing

Vincent C. H. Ma, Michael D. Mccool

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Tags: Algorithms, Computer science, Hashing, Rendering

January 7, 2011 by hgpu

Message passing on data-parallel architectures

Jeff A. Stuart, John D. Owens

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Tags: Computer science, GPU cluster, MPI, Networks, nVidia, nVidia GeForce GTX 280

January 6, 2011 by hgpu

Hardware-accelerated parallel non-photorealistic volume rendering

Eric B. Lum, Kwan-Liu Ma

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Tags: Computer science, nVidia, nVidia GeForce 3, Rendering, Visualization

January 6, 2011 by hgpu

Interactive volume illustration

Z. Nagy, J. Schneider, R. Westermann

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 4, OpenGL, Rendering

January 6, 2011 by hgpu

An asymmetric distributed shared memory model for heterogeneous parallel systems

Isaac Gelado, John E. Stone, Javier Cabezas, Sanjay Patel, Nacho Navarro, Wen-mei W. Hwu

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Tags: Computer science, CUDA, Memory, Memory model, nVidia, nVidia GeForce GTX 280

January 6, 2011 by hgpu

Efficient gather and scatter operations on graphics processors

Bingsheng He, Naga K. Govindaraju, Qiong Luo, Burton Smith

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce 8800, Search, Sorting, Sparse matrix

January 6, 2011 by hgpu

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

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high performance computing on graphics processing units: hgpu.org

Applications

Thousand core chips: a technology perspective

A Unified Runtime System for Heterogeneous Multi-core Architectures

JCUDA: A Programmer-Friendly Interface for Accelerating Java Programs with CUDA

Power Consumption of GPUs from a Software Perspective

Data transformations enabling loop vectorization on multithreaded data parallel architectures

Fast BVH Construction on GPUs

Low latency photon mapping using block hashing

Message passing on data-parallel architectures

Hardware-accelerated parallel non-photorealistic volume rendering

Interactive volume illustration

An asymmetric distributed shared memory model for heterogeneous parallel systems

Efficient gather and scatter operations on graphics processors

Recent source codes

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KISim: Kubernetes Intelligent Scheduling Simulator

Efficient GPU Implementation of Multi-Precision Integer Division

exa-AMD: Exascale Accelerated Materials Discovery

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

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