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Challenges Adapting CUDA PIC Codes to multiple GPUs

Olav Emil Eiksund

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Tags: Benchmarking, CUDA, Electrostatics, FFT, nVidia, nVidia GeForce GTX 980, OpenMP, Particle simulation, Particle-in-cell methods, Physics, Plasma physics, Tesla K20, Thesis

December 19, 2015 by hgpu

Efficient Query Processing in Co-Processor-accelerated Databases

Sebastian Bress

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Tags: Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia GeForce GT 640, Package, Tesla C1060, Tesla C2050, Thesis

December 19, 2015 by hgpu

A CUDA Kernel Scheduler Exploiting Static Data Dependencies

Eva Burrows

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Tags: Computer science, CUDA, nVidia, Task scheduler

December 15, 2015 by hgpu

Run-time support for multi-level disjoint memory address spaces

Javier Bueno Hedo

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Tags: Computer science, CUDA, MPI, nVidia, nVidia GeForce GTX 480, OmpSs, OpenMP, Thesis

December 15, 2015 by hgpu

Compressed Dynamic Mode Decomposition for Real-Time Object Detection

N. Benjamin Erichson, Steven L. Brunton, J. Nathan Kutz

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 950 M, Sensing

December 15, 2015 by hgpu

Transforming C OpenMP Programs for Verification in CIVL

Michael Rogers

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Tags: Computer science, CUDA, MPI, nVidia, OpenCL, OpenMP, Pthreads, Thesis

December 10, 2015 by hgpu

MapGraph: A High Level API for Fast Development of High Performance Graph Analytics on GPUs

Zhisong Fu, Michael Personick, Bryan Thompson

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

December 10, 2015 by hgpu

Deep Speech 2: End-to-End Speech Recognition in English and Mandarin

Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro K 1200, Package, Speech recognition

December 10, 2015 by hgpu

High Performance Histograms on SIMT and SIMD Architectures

M.E.R. Berger

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Tags: AMD Radeon R9 290X, Computer science, CUDA, nVidia, nVidia GeForce GTX 570, nVidia GeForce GTX 660, nVidia GeForce GTX 750, OpenCL, Performance, Thesis

December 10, 2015 by hgpu

Join Execution Using Fragmented Columnar Indices on GPU and MIC

Elena V. Ivanova, Stepan O. Prikazchikov, Leonid B. Sokolinsky

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Tags: Computer science, CUDA, Databases, Intel Xeon Phi, nVidia, Tesla K40

December 10, 2015 by hgpu

A Parallel Solver for Markov Decision Process in Crowd Simulations

Sergio Ruiz, Benjamin Hernandez

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Tags: ARM, Computer science, Crowd simulation, CUDA, nVidia, nVidia GeForce GTX Titan, nVidia Jetson TK1, Path problems, Tesla K40, Thrust

December 9, 2015 by hgpu

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, Zheng Zhang

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 980, Package

December 8, 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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