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Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

Giorgis Georgakoudis, Charles J. Gillan, Ahmed Sayed, Ivor Spence, Richard Faloon, Dimitrios S. Nikolopoulos

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Tags: ARM, Computer science, Finance, Intel Xeon Phi, Option pricing

January 5, 2015 by hgpu

GPU: Power vs Performance

Siddhartha Sankar Mondal

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 580, Thesis

January 5, 2015 by hgpu

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Edoardo Paone, Francesco Robino, Gianluca Palermo, Vittorio Zaccaria, Ingo Sander, Cristina Silvano

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia Quadro NVS 300, OpenCL, Performance

January 2, 2015 by hgpu

Disjunctive Normal Networks

Mehdi Sajjadi, Mojtaba Seyedhosseini, Tolga Tasdizen

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Tags: Computer science, Computer vision, CUDA, Machine learning, Neural and Evolutionary Computing, Neural networks, nVidia

January 2, 2015 by hgpu

Characterization of OpenCL on a Scalable FPGA Architecture

Shanyuan Gao, Jeremy Chritz

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Tags: AES, Computer science, FPGA, OpenCL

December 30, 2014 by hgpu

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

Florentino Sainz, Sergi Mateo, Vicenc Beltran, Jose L. Bosque, Xavier Martorell, Eduard Ayguade

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Tags: Computer science, CUDA, Fortran, nVidia, OpenCL, Tesla M2050

December 30, 2014 by hgpu

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Saeed Taheri

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Thesis

December 30, 2014 by hgpu

Spectral classification using convolutional neural networks

Pavel Hala

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Tags: Astrophysics, Computer science, CUDA, Instrumentation and Methods for Astrophysics, Machine learning, Neural and Evolutionary Computing, nVidia, Thesis

December 30, 2014 by hgpu

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

Jonathan Passerat-Palmbach (ISIMA, UBP, LIMOS), David Hill (LIMOS, UBP, ISIMA)

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Source codes

Tags: Computer science, CUDA, nVidia, Package, Pseudo-random number generators, Stochastic simulation

December 30, 2014 by hgpu

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Vajira Thambawita, Roshan Ragel, Dhammika Elkaduwe

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, Performance, String matching

December 30, 2014 by hgpu

Automatic Tuning of Local Memory Use on GPGPUs

Tianyi David Han, Tarek S. Abdelrahman

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Tags: Benchmarking, Computer science, Machine learning, nVidia, OpenCL, Performance, Tesla M2090

December 26, 2014 by hgpu

Accelerating Correlation Power Analysis Using Graphics Processing Units

Hasindu Gamaarachchi, Roshan Ragel, Darshana Jayasinghe

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Tags: AES, Algorithms, Computer science, CUDA, nVidia, Performance, Security, Tesla C2075

December 26, 2014 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

Methods and Metrics for Fair Server Assessment under Real-Time Financial Workloads

GPU: Power vs Performance

Customization of OpenCL Applications for Efficient Task Mapping under Heterogeneous Platform Constraints

Disjunctive Normal Networks

Characterization of OpenCL on a Scalable FPGA Architecture

Extending OmpSs to support CUDA and OpenCL in C, C++ and Fortran Applications

A Tool for Automatic Suggestions for Irregular GPU Kernel Optimization

Spectral classification using convolutional neural networks

How to Correctly Deal With Pseudorandom Numbers in Manycore Environments – Application to GPU programming with Shoverand

To Use or Not to Use: Graphics Processing Units for Pattern Matching Algorithms

Automatic Tuning of Local Memory Use on GPGPUs

Accelerating Correlation Power Analysis Using Graphics Processing Units

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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