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Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Kalin Ovtcharov, Olatunji Ruwase, Joo-Young Kim, Jeremy Fowers, Karin Strauss, Eric S. Chung

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Tags: Computer science, FPGA, Machine learning, Neural networks, Speech recognition

February 27, 2015 by hgpu

Face Detection on CUDA

Raksha Patel, Isha Vajani

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GT 410 M

February 27, 2015 by hgpu

A Graph-Partition-Based Scheduling Policy for Heterogeneous Architectures

Hao Wu, Daniel Lohmann, Wolfgang Schroder-Preikschat

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, Task scheduling

February 27, 2015 by hgpu

Very Fast Non-Dominated Sorting

Czeslaw Smutnicki, Jaroslaw Rudy, Dominik Zelazny

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, Sorting, Tesla K20

February 24, 2015 by hgpu

Raster2Mesh: Rasterization based CVT meshing

Jonas Martinez, Frederic Claux, Sylvain Lefebvre

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX Titan, OpenGL, Rasterization, Tessellation, Voronoi diagram

February 24, 2015 by hgpu

A Vision for GPU-accelerated Parallel Computation on Geo-Spatial Datasets

Sushil K. Prasad, Michael McDermott, Satish Puri, Dhara Shah, Danial Aghajarian, Shashi Shekhar, Xun Zhou

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Tags: Computer science, CUDA, Databases, nVidia

February 24, 2015 by hgpu

A Virtual Machine Model for Accelerating Relational Database Joins using a General Purpose GPU

Kevin Angstadt, Ed Harcourt

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 460, nVidia GeForce GTX 760

February 24, 2015 by hgpu

Characterising Bipartite Graph Matching Algorithms on GPUs

Stanley Tsang

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Tags: Algorithms, Computer science, CUDA, Graph theory, nVidia, Tesla K20, Thesis

February 23, 2015 by hgpu

Investigation of the OpenCL SYCL Programming Model

Angelos Trigkas

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, OpenCL, Thesis

February 23, 2015 by hgpu

Stochastic Gradient Descent on GPUs

Rashid Kaleem, Sreepathi Pai, Keshav Pingali

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Tags: Algorithms, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla K40

February 22, 2015 by hgpu

High performance methods for frequent pattern mining

Lan Vu

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Tags: Computer science, CUDA, Data mining, Databases, nVidia, Tesla C2050, Thesis

February 22, 2015 by hgpu

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Ang Li, Hammad Mazhar, Radu Serban, Dan Negrut

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Tags: Computer science, CUDA, Linear Algebra, nVidia, OpenCL, Performance, Python, Sparse matrix, Tesla K20

February 22, 2015 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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

Accelerating Deep Convolutional Neural Networks Using Specialized Hardware

Face Detection on CUDA

A Graph-Partition-Based Scheduling Policy for Heterogeneous Architectures

Very Fast Non-Dominated Sorting

Raster2Mesh: Rasterization based CVT meshing

A Vision for GPU-accelerated Parallel Computation on Geo-Spatial Datasets

A Virtual Machine Model for Accelerating Relational Database Joins using a General Purpose GPU

Characterising Bipartite Graph Matching Algorithms on GPUs

Investigation of the OpenCL SYCL Programming Model

Stochastic Gradient Descent on GPUs

High performance methods for frequent pattern mining

Comparison of SPMV performance on matrices with different matrix format using CUSP, cuSPARSE and ViennaCL

Recent source codes

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

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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