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GPU Computing to Improve Game Engine Performance

Abu Asaduzzaman, Hin Y. Lee

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Tags: Computer science, CUDA, Data parallelism, Games, Image processing, nVidia, nVidia GeForce 8800 GTX, Performance

July 28, 2014 by hgpu

Performance-efficient mechanisms for managing irregularity in throughput processors

Minsoo Rhu

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Tags: Computer science, CUDA, GPGPU-sim, nVidia, nVidia GeForce GTX 480, Performance, Prefetch, Thesis

July 20, 2014 by hgpu

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

Tsutomu Inamoto, Yoshinobu Higami, Shin-ya Kobayashi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, Performance

July 17, 2014 by hgpu

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

David Rohr

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Performance, Review, Thesis

July 14, 2014 by hgpu

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Blake Koop

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Tags: CUDA, Fluid dynamics, nVidia, Performance, Tesla C2070

July 14, 2014 by hgpu

Benchmarking the Memory Hierarchy of Modern GPUs

Xinxin Mei, Kaiyong Zhao, Chengjian Liu, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 780, Package, Performance

July 14, 2014 by hgpu

Understanding the SIMD Efficiency of Graph Traversal on GPU

Yichao Cheng, Hong An, Zhitao Chen, Feng Li, Zhaohui Wang, Xia Jiang, Yi Peng

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Tesla C2050

July 10, 2014 by hgpu

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

Hasse Lovgren

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Tags: ATI, ATI Radeon HD 5870, Computer science, Mathematics, Neural networks, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Tesla C1060, Thesis

July 9, 2014 by hgpu

On Static Timing Analysis of GPU Kernels

Vesa Hirvisalo

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Tags: Computer science, OpenCL, Performance, Timing analysis

July 4, 2014 by hgpu

SIMD Implementation of a Multiplicative Schwarz Smoother for a Multigrid Poisson Solver on an Intel Xeon Phi Coprocessor

Masatoshi Kawai, Takeshi Iwashita, Hiroshi Nakashima

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Tags: Computer science, Intel Xeon Phi, Performance, Poisson equation

July 4, 2014 by hgpu

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Shahzeb Siddiqui, Saber Feki

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Tags: Computer science, CUDA, nVidia, OpenACC, Performance, Tesla K20

July 3, 2014 by hgpu

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Langshi Chen, Serge Petiton, Leroy Drummond, Maxime Hugues

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla K20

July 3, 2014 by hgpu

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

PTXBench: Benchmark and Adapt LLMs for GPU Kernel Optimization with Architecture-specific PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

Compiler-Grounded Hierarchical Diagnosis for LLM-Based Triton Kernel Optimization

NVIDIA Object Oriented Agents

NVIDIA-labs OO Agents: Native Python Object-Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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high performance computing on graphics processing units: hgpu.org

GPU Computing to Improve Game Engine Performance

Performance-efficient mechanisms for managing irregularity in throughput processors

Optimal Periods for Probing Convergence of Infinite-stage Dynamic Programmings on GPUs

On Development, Feasibility, and Limits of Highly Efficient CPU and GPU Programs in Several Fields

GPU Techniques Applied to Euler Flow Simulations and Comparison to CPU Performance

Benchmarking the Memory Hierarchy of Modern GPUs

Understanding the SIMD Efficiency of Graph Traversal on GPU

Utilizing state-of-art NeuroES and GPGPU to optimize Mario AI

On Static Timing Analysis of GPU Kernels

SIMD Implementation of a Multiplicative Schwarz Smoother for a Multigrid Poisson Solver on an Intel Xeon Phi Coprocessor

Historic Learning Approach for Auto-tuning OpenACC Accelerated Scientific Applications

Toward Auto-tuned Krylov Basis Computations with minimized Communication on Clusters of Accelerators

Recent source codes

PTXBench: an open-source environment for kernel agents with architecture-specific CUDA/PTX

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

TensorCorePTX: PTX Tensor Core GEMM Exploration

FlashPDE: Triton-fused PDE stencil kernels for physics-informed neural networks

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

NVIDIA Object Oriented Agents

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

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