high performance computing on graphics processing units: hgpu.org

Zachary DeVito, Michael Mara, Michael Zollhofer, Gilbert Bernstein, Jonathan Ragan-Kelley, Christian Theobalt, Pat Hanrahan, Matthew Fisher, Matthias Niessner

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Tags: Comnputer science, Computer vision, CUDA, Image generation, Image processing, nVidia, Programming Languages

April 26, 2016 by hgpu

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 by hgpu

A Parallel Solution to Finding Nodal Neighbors in Generic Meshes

Gang Mei, Nengxiong Xu, Hong Tian

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640

April 19, 2016 by hgpu

MIML Learning with CNNs: Yelp Restaurant Photo Classification

Pulkit Agrawal, Raghav Gupta

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Tags: CNN, Computer science, CUDA, Deep learning, Intel Xeon Phi, nVidia

April 19, 2016 by hgpu

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

Yongchao Liu, Srinivas Aluru

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Source codes

Tags: Algorithms, Computer science, CUDA, Intel Xeon Phi, nVidia, Package, Performance, PTX, Tesla K40

April 19, 2016 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Exposing Errors Related to Weak Memory in GPU Applications

On the design of sparse hybrid linear solvers for modern parallel architectures

Adaptive GPU Array Layout Auto-Tuning

Parallel Subgraph Mining on Hybrid Platforms: HPC Systems, Multi-Cores and GPUs

GPU-Aware Non-contiguous Data Movement In Open MPI

Investigating performance portability of a highly scalable particle-in-cell simulation code on various multi-core architectures

CMA-ES for Hyperparameter Optimization of Deep Neural Networks

Opt: A Domain Specific Language for Non-linear Least Squares Optimization in Graphics and Imaging

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

A Parallel Solution to Finding Nodal Neighbors in Generic Meshes

MIML Learning with CNNs: Yelp Restaurant Photo Classification

LightScan: Faster Scan Primitive on CUDA Compatible Manycore Processors

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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