high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Simultaneous Branch and Warp Interweaving for Sustained GPU Performance

Nicolas Brunie, Sylvain Collange, Gregory Diamos

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, Performance

December 15, 2011 by hgpu

Performance in GPU Architectures: Potentials and Distances

Ahmad Lashgar, Amirali Baniasadi

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance

December 15, 2011 by hgpu

Graph Generation on GPUs using Dynamic Memory Allocation

A. Leist, K.A. Hawick

View

Download (PDF)

Tags: Algorithms, Benchmarking, Computer science, CUDA, Graph theory, Memory model, nVidia, nVidia GeForce GTX 580, Performance

December 14, 2011 by hgpu

Rethinking Runtime Verification on Hundreds of Cores: Challenges and Opportunities

Tayfun Elmas, Semih Okur, Serdar Tasiran

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 465, Performance

December 14, 2011 by hgpu

Evaluating graph coloring on GPUs

A.V. Pascal Grosset, Peihong Zhu, Shusen Liu, Suresh Venkatasubramanian, Mary Hall

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Performance, Programming techniques

December 11, 2011 by hgpu

Fast and Memory-Efficient Minimum Spanning Tree on the GPU

Scott Rostrup, Shweta Srivastava, Kishore Singhal

View

Download (PDF)

Tags: Algorithms, Computer science, Graph theory, nVidia, Performance, Tesla S1070, Tesla T10

December 10, 2011 by hgpu

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Qiang Liu, Wayne Luk

View

Download (PDF)

Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, Performance, Tesla C2070

December 9, 2011 by hgpu

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Petr Pospichal

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTX 480, Performance

December 7, 2011 by hgpu

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Jan Fousek, Jiri Filipovic, Matus Madzin

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 6, 2011 by hgpu

Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications

Shubham Gupta, M.Rajasekhara Babu

View

Download (PDF)

Tags: Computer science, CUDA, High-level Languages, nVidia, nVidia GeForce GT 210 M, OpenMP, Performance, String matching

December 6, 2011 by hgpu

Performance engineering for the Lattice Boltzmann method on GPGPUs: Architectural requirements and performance results

Johannes Habich, Christian Feichtinger, Harald Kostler, Georg Hager, Gerhard Wellein

View

Download (PDF)

Tags: Algorithms, ATI, ATI Radeon HD 6970, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce 8800 GTX, OpenCL, Optimization, Performance, Tesla C1060, Tesla C2070

December 6, 2011 by hgpu

GMM based Fisher vector calculation on GPGPU

Erik Bodzsar, Balint Daroczy, Istvan Petras, Andras A. Benczur

View

Download (PDF)

Source codes

Tags: Clustering, CUDA, Databases, Image processing, nVidia, nVidia GeForce GTX 285, Package, Performance, SIFT

December 5, 2011 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Simultaneous Branch and Warp Interweaving for Sustained GPU Performance

Performance in GPU Architectures: Potentials and Distances

Graph Generation on GPUs using Dynamic Memory Allocation

Rethinking Runtime Verification on Hundreds of Cores: Challenges and Opportunities

Evaluating graph coloring on GPUs

Fast and Memory-Efficient Minimum Spanning Tree on the GPU

Objective-Driven Workload Allocation in Heterogeneous Computing Systems

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Performance Analysis of GPU compared to Single-core and Multi-core CPU for Natural Language Applications

Performance engineering for the Lattice Boltzmann method on GPGPUs: Architectural requirements and performance results

GMM based Fisher vector calculation on GPGPU

Recent source codes

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

Most viewed papers (last 30 days)