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Accelerating data mining workloads: current approaches and future challenges in system architecture design

Alok N. Choudhary, Daniel Honbo, Prabhat Kumar, Berkin Ozisikyilmaz, Sanchit Misra, Gokhan Memik

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Tags: Computer science, CUDA, Data mining, FPGA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT

September 30, 2011 by hgpu

Many-threaded implementation of differential evolution for the CUDA platform

Pavel Kromer, Vaclav Snasel, Jan Platos, Ajith Abraham

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential evolution, Genetic programming, nVidia, Optimization, Tesla C2050

September 29, 2011 by hgpu

Active thread compaction for GPU path tracing

Ingo Wald

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Presentation, Raytracing

September 29, 2011 by hgpu

Evolving CUDA PTX programs by quantum inspired linear genetic programming

Leandro F. Cupertino, Cleomar P. Silva, Douglas M. Dias, Marco Aurelio C. Pacheco, Cristiana Bentes

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Tags: Computer science, CUDA, Databases, Genetic programming, nVidia, Performance, PTX, Tesla C1060

September 29, 2011 by hgpu

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

L. Lin, Chung-Sang Ng, A. Bhattacharjee

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Tags: Astrophysics, Computational Physics, CUDA, GPU cluster, Instrumentation and Methods for Astrophysics, Magnetohydrodynamics, MPI, nVidia, Plasma physics, Solar and Stellar Astrophysics, Spectral methods, Tesla C2050

September 29, 2011 by hgpu

Possible planet-forming regions on submillimetre images

Zsolt Regaly, A. Juhasz, Zs. Sandor, C. P. Dullemond

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Source codes

Tags: Astrophysics, CUDA, Image processing, nVidia, nVidia GeForce GTX 280, Package, Solar and Stellar Astrophysics

September 29, 2011 by hgpu

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Da-Qi Ren, Reiji Suda

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 8800 GTS, Optimization, Tesla C2050

September 28, 2011 by hgpu

Parallelizing fuzzy rule generation using GPGPU

Takesuke Uenishi, Tomoharu Nakashima and Noriyuki Fujimoto

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 295, Optimization, Performance

September 28, 2011 by hgpu

VoxelPipe: a programmable pipeline for 3D voxelization

Jacopo Pantaleoni

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Raytracing, Sorting, Voxelization

September 28, 2011 by hgpu

Thread Block Compaction for Efficient SIMT Control Flow

Wilson W. L. Fung, Tor M. Aamodt

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Tags: Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, Programming techniques

September 28, 2011 by hgpu

Parallel implementations of probabilistic latent semantic analysis on graphic processing units

Hang Chen

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Tags: Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Text mining, Thesis

September 27, 2011 by hgpu

Fast On-line Statistical Learning on a GPGPU

FangZhou Xiao, Eric McCreath, Christfried Webers

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Tags: Algorithms, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 200, nVidia GeForce GTX 295, Stochastic simulation

September 27, 2011 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

See all packages

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high performance computing on graphics processing units: hgpu.org

Accelerating data mining workloads: current approaches and future challenges in system architecture design

Many-threaded implementation of differential evolution for the CUDA platform

Active thread compaction for GPU path tracing

Evolving CUDA PTX programs by quantum inspired linear genetic programming

Large-Scale High-Lundquist Number Reduced MHD Simulations of the Solar Corona Using GPU Accelerated Machines

Possible planet-forming regions on submillimetre images

Global optimization model on power efficiency of GPU and multicore processing element for SIMD computing with CUDA

Parallelizing fuzzy rule generation using GPGPU

VoxelPipe: a programmable pipeline for 3D voxelization

Thread Block Compaction for Efficient SIMT Control Flow

Parallel implementations of probabilistic latent semantic analysis on graphic processing units

Fast On-line Statistical Learning on a GPGPU

Recent source codes

CrossTL: Universal Programming Language & Translator

TBD-GPU

DG-SWEM - The Discontinuous Galerkin Shallow Water Equation Model

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

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