Programming

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A Parallel Algorithm to Test Chordality of Graphs

Agnieszka Lupinska

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Tags: Computer science, CUDA, Data Structures and Algorithms, Graph theory, nVidia, nVidia GeForce GTX 560 Ti, Thesis

August 28, 2015 by hgpu

CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

Gang Mei

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Tags: Computational Geometry, Computer science, CUDA, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

gScan: Accelerating Graham Scan on the GPU

Gang Mei

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Tags: Algorithms, Computational Geometry, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GT 640, nVidia GeForce GTX 660 M, Sorting

August 27, 2015 by hgpu

Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

C. A. Navarro, Huang Wei, Youjin Deng

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Tags: Algorithms, Computational Physics, CUDA, Ising model, Monte Carlo simulation, nVidia, Physics, Spin Systems, Tesla K40

August 27, 2015 by hgpu

MemcachedGPU: Scaling-up Scale-out Key-value Stores

Tayler H. Hetherington, Mike O'Connor, Tor M. Aamodt

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Tags: Computer science, CUDA, Databases, Energy-efficient computing, nVidia, nVidia GeForce GTX 750 Ti, Package, Tesla K20, Tesla K40

August 27, 2015 by hgpu

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Shin Morishima, Hiroki Matsutani

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 980, Performance

August 24, 2015 by hgpu

Viability of Feature Detection on Sony Xperia Z3 using OpenCL

Max Danielsson, Thomas Sievert

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Tags: Android, Computer science, Computer vision, Embedded high-performance computing, nVidia, nVidia GeForce GTX 660, OpenCL, Package, Thesis

August 24, 2015 by hgpu

Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models

Xiangyun Hu, Lizhi Ye, Shiyan Pang, Jie Shan

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 690, Sensing

August 24, 2015 by hgpu

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

Mehdi Amini

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Tags: ATI, ATI Radeon HD 6970, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 670, OpenCL, Tesla C1060, Tesla C2070, Thesis

August 24, 2015 by hgpu

Scheduling for new computing platforms with GPUs

Florence Monna

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Tags: Computer science, Data Structures and Algorithms, nVidia, OpenCL, Task scheduling, Tesla C2050, Thesis

August 24, 2015 by hgpu

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

Staff of Berkeley Design Technology

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Tags: Algorithms, ARM, Computer science, Computer vision, OpenCL

August 21, 2015 by hgpu

Locality Aware Work-Stealing Based Scheduling in Hybrid CPU-GPU

A. Tarun Beri, B. Sorav Bansal, C. Subodh Kumar

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Tags: Computer science, CUDA, Distributed computing, nVidia, Task scheduling, Tesla M2070

August 21, 2015 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Programming

A Parallel Algorithm to Test Chordality of Graphs

CudaChain: A Practical GPU-accelerated 2D Convex Hull Algorithm

gScan: Accelerating Graham Scan on the GPU

Adaptive Multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

MemcachedGPU: Scaling-up Scale-out Key-value Stores

Performance Evaluations of Document-Oriented Databases using GPU and Cache Structure

Viability of Feature Detection on Sony Xperia Z3 using OpenCL

Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models

Source-to-Source Automatic Program Transformations for GPU-like Hardware Accelerators

Scheduling for new computing platforms with GPUs

Implementing Computer Vision Functions with OpenCL on the Qualcomm Adreno 420

Locality Aware Work-Stealing Based Scheduling in Hybrid CPU-GPU

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Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

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