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GPU Based Methods for Interactive Information Visualization of Big Data

Peng Mi

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 680, OpenGL, Thesis, Visualization

January 29, 2016 by hgpu

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

Tobias Klein

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, Image processing, nVidia, nVidia Quadro 6000, OpenCL, Thesis, Visualization

January 29, 2016 by hgpu

GPU-Accelerated Recurrent Neural Networks: OpenCLLink and SymbolicC

Zdenek Buk

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Tags: Computer science, Deep learning, Machine learning, Neural networks, nVidia, OpenCL, Package, RNN

January 29, 2016 by hgpu

Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search

Gang Mei, Nengxiong Xu, Liangliang Xu

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Tags: Algorithms, Computer science, CUDA, Nearest neighbour, nVidia, nVidia GeForce GT 730 M

January 26, 2016 by hgpu

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Francisco Javier Ordonez, Daniel Roggen

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Tags: Computer science, Deep learning, LSTM, Machine learning, Neural networks, Package, Python, RNN, Theano

January 26, 2016 by hgpu

Compositional Compilation for Sparse, Irregular Data Parallelism

Adam Harries, Michel Steuwer, Murray Cole, Alan Gray, Christophe Dubach

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Tags: Computer science, Data parallelism, nVidia, OpenCL, Sparse matrix, Tesla K40

January 26, 2016 by hgpu

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

Kyungjoo Kim, Sivasankaran Rajamanickam, George Stelle, H. Carter Edwards, Stephen L. Olivier

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Tags: Algorithms, Computer science, Factorization, Intel Xeon Phi, Mathematical Software, Package, Sparse matrix

January 26, 2016 by hgpu

Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer

Alina Sirbu, Ozalp Babaoglu

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Tags: Computer science, Energy-efficient computing, Intel Xeon Phi, Package, Python, Task scheduling

January 26, 2016 by hgpu

Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts

Joshua Dennis Booth, Sivasankaran Rajamanickam, Heidi K. Thornquist

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Tags: Algorithms, Computer science, Factorization, Intel Xeon Phi, Sparse direct solvers, Sparse matrix

January 22, 2016 by hgpu

GPU Multisplit

Saman Ashkiani, Andrew Davidson, Ulrich Meyer, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 750 Ti, Tesla K40

January 22, 2016 by hgpu

Parallel Explicit FEM Algorithms Using GPU’s

Seyed Parsa Banihashemi

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Tags: Algorithms, AMD Radeon R9 280X, ATI, ATI Radeon HD 7970, Computer science, FEM, Finite element method, nVidia, nVidia GeForce GTX Titan, OpenCL, Particle swarm optimization, Performance, Tesla M2090, Thesis

January 22, 2016 by hgpu

Heterogeneous (CPU+GPU) Working-set Hash Tables

Ziaul Choudhury, Suresh Purini

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Tags: Computer science, CUDA, Hashing, Heterogeneous systems, nVidia, Tesla K20

January 22, 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

TensorCorePTX: PTX Tensor Core GEMM Exploration

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

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

FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

PortLBM: Portable GPU-accelerated Lattice Boltzmann Method Simulations

PortLBM: A Portable Lattice Boltzmann Tool Leveraging SYCL on AMD, NVIDIA, and Intel GPUs

Harness Engineering for LLM-Driven GPU Kernel Generation

CANNBot Skills

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

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high performance computing on graphics processing units: hgpu.org

Applications

GPU Based Methods for Interactive Information Visualization of Big Data

Towards Interactive Visual Exploration of Parallel Programs using a Domain-specific Language

GPU-Accelerated Recurrent Neural Networks: OpenCLLink and SymbolicC

Improving GPU-accelerated Adaptive IDW Interpolation Algorithm Using Fast kNN Search

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

Compositional Compilation for Sparse, Irregular Data Parallelism

Task Parallel Incomplete Cholesky Factorization using 2D Partitioned-Block Layout

Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer

Basker: A Threaded Sparse LU Factorization Utilizing Hierarchical Parallelism and Data Layouts

GPU Multisplit

Parallel Explicit FEM Algorithms Using GPU’s

Heterogeneous (CPU+GPU) Working-set Hash Tables

Recent source codes

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

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

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