high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Computer science

N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks

Yudi Li, Min Tang, Yun Yang, Zi Huang, Ruofeng Tong, Shuangcai Yang, Yao Li, Dinesh Manocha

View

Download (PDF)

Tags: 3D Graphics and Realism, Machine learning, nVidia, nVidia GeForce RTX 3090, PyTorch

December 19, 2021 by hgpu

TCUDB: Accelerating Database with Tensor Processors

Yu-Ching Hu, Yuliang Li, Hung-Wei Tseng

View

Download (PDF)

Tags: Computer science, CUDA, Databases, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 3090

December 19, 2021 by hgpu

Evaluation of Pseudo-Random Number Generation on GPU Cards

Tair Askar, Bekdaulet Shukirgaliyev, Martin Lukac, Ernazar Abdikamalov

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 3080, nVidia GeForce RTX 3090, Pseudo-random number generators

December 19, 2021 by hgpu

Fast Neural Representations for Direct Volume Rendering

Sebastian Weiss, Philipp Hermüller, Rüdiger Westermann

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, CUDA, GLSL, nVidia, nVidia GeForce RTX 2070, Package, Raytracing, Rendering, Visualization

December 12, 2021 by hgpu

Manas: Mining Software Repositories to Assist AutoML

Giang Nguyen, Johir Islam, Rangeet Pan, Hridesh Rajan

View

Download (PDF)

Source codes

Tags: Computer science, Deep learning, Neural networks, nVidia, Package, Python, Software Engineering, Tesla V100

December 12, 2021 by hgpu

CitiusSynapse: A Deep Learning Framework for Embedded Systems

Seungtae Hong, Hyunwoo Cho, Jeong-Si Kim

View

Download (PDF)

Tags: Computer science, Deep learning, Embedded high-performance computing, OpenCL

December 12, 2021 by hgpu

High performance computing on Android devices – a case study

Robert Fritze, Claudia Plant

View

Download (PDF)

Tags: AMD Radeon VII, Android, ATI, Benchmarking, Computer science, HPC, nVidia GeForce Titan V, OpenCL

December 12, 2021 by hgpu

GPU backed Data Mining on Android Devices

Robert Fritze, Claudia Plant

View

Download (PDF)

Source codes

Tags: Android, Computer science, Data mining, HPC, Machine learning, OpenCL, Package

December 12, 2021 by hgpu

Analysis and Comparison of Performance and Power Consumption of Neural Networks on CPU, GPU, TPU and FPGA

Christopher Noel Hesse

View

Download (PDF)

Tags: Benchmarking, Computer science, Deep learning, FPGA, Neural networks, nVidia, nVidia DGX-1, nVidia GeForce RTX 2070, nVidia Jetson Nano, Performance, Tesla V100

December 5, 2021 by hgpu

Autotuning CUDA: Applying NLP Techniques to LS-CAT

Lars Bjertnes, Jacob O. Tørring, Anne C. Elster

View

Download (PDF)

Tags: Auto-Tuning, Computer science, CUDA, Machine learning, NLP, nVidia

December 5, 2021 by hgpu

An Auto-Programming Approach to Vulkan

Vladimir Frolov, Vadim Sanzharov, Vladimir Galaktionov, Alexandr Scherbakov

View

Download (PDF)

Tags: 3D Graphics and Realism, Code generation, nVidia, nVidia GeForce RTX 2080, Raytracing, Vulkan

December 5, 2021 by hgpu

Bayesian Optimization for auto-tuning GPU kernels

Floris-Jan Willemsen, Rob van Nieuwpoort, Ben van Werkhoven

View

Download (PDF)

Source codes

Tags: Bayesian, Computer science, CUDA, Machine learning, nVidia, nVidia A100, nVidia GeForce GTX Titan X, nVidia GeForce RTX 2070, OpenCL, Package, Performance

December 5, 2021 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

N-Cloth: Predicting 3D Cloth Deformation with Mesh-Based Networks

TCUDB: Accelerating Database with Tensor Processors

Evaluation of Pseudo-Random Number Generation on GPU Cards

Fast Neural Representations for Direct Volume Rendering

Manas: Mining Software Repositories to Assist AutoML

CitiusSynapse: A Deep Learning Framework for Embedded Systems

High performance computing on Android devices – a case study

GPU backed Data Mining on Android Devices

Analysis and Comparison of Performance and Power Consumption of Neural Networks on CPU, GPU, TPU and FPGA

Autotuning CUDA: Applying NLP Techniques to LS-CAT

An Auto-Programming Approach to Vulkan

Bayesian Optimization for auto-tuning GPU kernels

Recent source codes

FP4 FlashAttention forward, backward, and TorchTitan reproduction code

EinsummableV3 - graph-based computation with tensor operations support

MaxKernel: Intelligent TPU Kernel Engineering Agents

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

Most viewed papers (last 30 days)