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QPACE 2 and Domain Decomposition on the Intel Xeon Phi

Paul Arts, Jacques Bloch, Peter Georg, Benjamin Glaessle, Simon Heybrock, Yu Komatsubara, Robert Lohmayer, Simon Mages, Bernhard Mendl, Nils Meyer, Alessio Parcianello, Dirk Pleiter, Florian Rappl, Mauro Rossi, Stefan Solbrig, Giampietro Tecchiolli, Tilo Wettig, Gianpaolo Zanier

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Tags: Benchmarking, Computational Physics, Computer science, High Energy Physics - Lattice, Intel Xeon Phi

February 22, 2015 by hgpu

Reproducible Triangular Solvers for High-Performance Computing

Roman Iakymchuk, David Defour, Sylvain Collange, Stef Graillat

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Tags: Algorithms, Computer science, Linear Algebra, nVidia, nVidia Quadro K5000, OpenCL, Package, Tesla K20

February 19, 2015 by hgpu

Fast, Memory-Efficient Construction of Voxelized Shadows

Viktor Kampe, Erik Sintorn, Ulf Assarsson

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Tags: 3D Graphics and Realism, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan, OpenGL, Real-time graphics, Rendering

February 19, 2015 by hgpu

Auto-tuning Shallow water simulations on GPUs

Andre B. Amundsen

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, nVidia Quadro 1800 M, Rendering, Thesis

February 19, 2015 by hgpu

Memory-efficient Adaptive Subdivision for Software Rendering on the GPU

Thomas Weber

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Tags: ATI, ATI Radeon HD 7970, Computer science, OpenCL, Package, Rendering, Tessellation

February 19, 2015 by hgpu

NUPAR: A Benchmark Suite for Modern GPU Architectures

Yash Ukidave, Fanny Nina Paravecino, Leiming Yu, Charu Kalra, Amir Momeni, Zhongliang Chen, Nick Materise, Brett Daley, Perhaad Mistry, David Kaeli

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Tags: ATI, ATI Radeon HD 7970, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenCL, Package, Tesla C2070, Tesla K40

February 13, 2015 by hgpu

Locally-Oriented Programming: A Simple Programming Model for Stencil-Based Computations on Multi-Level Distributed Memory Architectures

Craig Rasmussen, Matthew Sottile, Daniel Nagle, Soren Rasmussen

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Tags: Computer science, OpenCL, Programming Languages

February 13, 2015 by hgpu

Quadratic Pseudo-Boolean Optimization for Scene Analysis using CUDA

Andreas Bauer

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX 450 Ti, Thesis

February 13, 2015 by hgpu

Large-Scale Deep Learning on the YFCC100M Dataset

Karl Ni, Roger Pearce, Kofi Boakye, Brian Van Essen, Damian Borth, Barry Chen, Eric Wang

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Tags: Computer science, Computer vision, CUDA, Deep learning, Machine learning, Neural networks, nVidia, Tesla M2050

February 13, 2015 by hgpu

Primal Dual Affine Scaling on GPUs

Nithish Divakar

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Tags: Computer science, CUDA, Numerical Analysis, nVidia, Tesla S1070

February 13, 2015 by hgpu

FSCL: Homogeneous programming, scheduling and execution on heterogeneous platforms

Gabriele Cocco

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Tags: ATI, ATI Radeon HD 7970, Computer science, Heterogeneous systems, OpenCL, Package, Thesis

February 10, 2015 by hgpu

GPU-accelerated HMM for Speech Recognition

Leiming Yu, Yash Ukidave, David Kaeli

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 680, nVidia GeForce GTX Titan, Package, Speech recognition

February 10, 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

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

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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