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Automatic SIMD Code Generation

Roland Leissa

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Tags: Algorithms, Code generation, Computer science, Optimization, Performance, Software Engineering, Thesis

January 4, 2012 by hgpu

Minimising Testing in Genetic Programming

W. B. Langdon

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, Software Engineering

December 15, 2011 by hgpu

GPU-Based Image Processing Use Cases: A High-Level Approach

Volkmar Wieser, Clemens Grelck, Holger Schoner, Peter Haslinger, Karoly Bosa, Bernhard Moser

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Tags: Benchmarking, CUDA, Image processing, nVidia, nVidia GeForce GT 425 M, Software Engineering, Virtualization

November 21, 2011 by hgpu

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Basile Starynkevitch

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Tags: Compilers, Computer science, OpenCL, Optimization, Programming Languages, Software Engineering

November 7, 2011 by hgpu

An Adaptive Framework for Managing Heterogeneous Many-Core Clusters

Muhammad Mustafa Rafique

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, MapReduce, nVidia, Prefetch, Software Engineering, Tesla C2050, Thesis

October 28, 2011 by hgpu

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

John Burns

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Tags: Computer science, CUDA, Databases, nVidia, OpenMP, Software Engineering

October 27, 2011 by hgpu

CUDA Application Design and Development

Rob Farber

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Tags: Book, Computer science, CUDA, nVidia, Review, Software Engineering

October 22, 2011 by hgpu

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Christian Motzing

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Tags: Computer science, CUDA, Molecular dynamics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Review, Software Engineering, Thesis

October 17, 2011 by hgpu

Highly Scalable Multi Objective Test Suite Minimisation Using Graphics Cards

Shin Yoo, Mark Harman, Shmuel Ur

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Tags: Algorithms, ATI, ATI Radeon HD 4850, Benchmarking, Computer science, OpenCL, Optimization, Software Engineering

September 28, 2011 by hgpu

2PARMA: Parallel Paradigms and Run-time Management Techniques for Many-Core Architectures

C.Silvano, W.Fornaciari, S.Crespi Reghizzi, G.Agosta, G.Palermo, V.Zaccaria, P.Bellasi, F.Castro, S.Corbetta, A.Di Biagio, E.Speziale, M. Tartara, D.Siorpaes, H.Hubert, B.Stabernack, J.Brandenburg, M.Palkovic, P.Raghavan, C.Ykman-Couvreur, A.Bartzas, S.Xydis, D.Soudris, T.Kempf, G.Ascheid, R.Leupers, H.Meyr, J.Ansari, P.Mahonen, B.Vanthournout

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Tags: Compilers, Computer science, Design space exploration, OpenCL, Performance, Programming techniques, Software Engineering

September 28, 2011 by hgpu

Unstructured grid applications on GPU: performance analysis and improvement

Lizandro Solano-Quinde, Zhi Jian Wang, Brett Bode, Arun K. Somani

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Software Engineering, Tesla T10

September 23, 2011 by hgpu

Debugging CUDA

William B. Langdon

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Tags: Computer science, CUDA, nVidia, Software Engineering

September 19, 2011 by hgpu

HipKittens: Fast and Furious AMD Kernels

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

An MLIR pipeline for offloading Fortran to FPGAs via OpenMP

mt4g: Memory Topology 4 GPUs

MT4G: A Tool for Reliable Auto-Discovery of NVIDIA and AMD GPU Compute and Memory Topologies

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

A High-Throughput GPU Framework for Adaptive Lossless Compression of Floating-Point Data

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

OpScanner

A Study of Floating-Point Precision Tuning in Deep Learning Operators Implementations

Atlas CLI: Machine Learning (ML) Lifecycle & Transparency Manager

Scalable GPU-Based Integrity Verification for Large Machine Learning Models

transformers_tvm: Implementation of Encoder Decoder transformer on TVM

Enhancing Transformer Performance and Portability through Auto-tuning Frameworks

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