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Understanding the Topics and Challenges of GPU Programming by Classifying and Analyzing Stack Overflow Posts

Wenhua Yang, Chong Zhang, Minxue Pan

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Tags: Computer science, CUDA, nVidia, OpenCL, Programming Languages, survey

December 10, 2023 by hgpu

Efficiently Processing Large Relational Joins on GPUs

Bowen Wu, Dimitrios Koutsoukos, Gustavo Alonso

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Tags: Benchmarking, Computer science, CUDA, Databases, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package

December 10, 2023 by hgpu

Edge AI for Internet of Energy: Challenges and Perspectives

Yassine Himeur, Aya Nabil Sayed, Abdullah Alsalemi, Faycal Bensaali, Abbes Amira

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Tags: Artificial intelligence, Computer science, Energy-efficient computing, Review

December 10, 2023 by hgpu

Compiler-centric across-stack deep learning acceleration

Perry Gibson

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Tags: Compilers, Computer science, Deep learning, Design space exploration, nVidia, nVidia Jetson AGX Xavier, nVidia Titan RTX, Thesis

December 10, 2023 by hgpu

Testing and Mutation Testing for GPU Kernels

Yujie Liu

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Tags: Benchmarking, Computer science, CUDA, nVidia, Package, Performance, Thesis

December 3, 2023 by hgpu

A Review of the Parallelization Strategies for Iterative Algorithms

Xingxing Zhou, Ming Ling, Shidi Tang, YanXiang Zhu

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, Data parallelism, OpenCL

December 3, 2023 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

Jun Chen, Xule Zhou, Hyesoon Kim

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Tags: AMD Radeon Instinct MI210, ATI, Code generation, Computer science, CUDA, HIP, nVidia, OpenCL, Package

December 3, 2023 by hgpu

A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures

Fabrizio Ferrandi, Serena Curzel, Leandro Fiorin, Daniele Ielmini, Cristina Silvano, Francesco Conti, Alessio Burrello, Francesco Barchi, Luca Benini, Luciano Lavagno, Teodoro Urso, Enrico Calore, Sebastiano Fabio Schifano, Cristian Zambelli, Maurizio Palesi, Giuseppe Ascia, Enrico Russo, Nicola Petra, Davide De Caro, Gennaro Di Meo, Valeria Cardellini, Salvatore Filippone, Francesco Lo Presti, Francesco Silvestri, Paolo Palazzari, Stefania Perri

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Tags: AI, Artificial intelligence, Computer science, CUDA, Deep learning, Design space exploration, Hardware Architecture, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia H100, OpenCL, survey