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A Survey of Techniques for Improving Security of Non-volatile Memories

Sparsh Mittal, Ahmed Alsalibi

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Tags: Computer science, Hardware security, non-volatile memory, Security, survey

February 15, 2018 by sparsh0mittal

Accelerating Interpreted Programming Languages on GPUs with Just-In-Time Compilation and Runtime Optimisations

Juan Jose Fumero Alfonso

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Tags: AMD Radeon R9 295X2, ATI, Computer science, Java, nVidia, nVidia GeForce GTX Titan Black, OpenCL, R, Thesis

February 15, 2018 by hgpu

TVM: End-to-End Optimization Stack for Deep Learning

Tianqi Chen, Thierry Moreau, Ziheng Jiang, Haichen Shen, Eddie Yan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, Arvind Krishnamurthy

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, performance portability, TensorFlow, Tesla K80

February 15, 2018 by hgpu

Improving Locality of Unstructured Mesh Algorithms on GPUs

Andras Attila Sulyok, Gabor Daniel Balogh, Istvan Zoltan Reguly, Gihan R. Mudalige

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Tags: Algorithms, Computer science, CUDA, Finite element method, Mathematical Software, nVidia, Performance, Tesla P100

February 15, 2018 by hgpu

GPU Accelerated Finite Element Assembly with Runtime Compilation

Tao Cui, Xiaohu Guo, Hui Liu

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Tags: Computer science, CUDA, Differential equations, FEM, Finite element method, Mathematical Software, Numerical Analysis, nVidia, Partial differential equations, PDEs, Symbolic Computation, Tesla K20, Tesla M2090, Tesla V100

February 15, 2018 by hgpu

Using Meta-heuristics and Machine Learning for Software Optimization of Parallel Computing Systems: A Systematic Literature Review

Suejb Memeti, Sabri Pllana, Alecio Binotto, Joanna Kolodziej, and Ivona Brandic

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Tags: Computer science, Machine learning, Metaheuristics, parallel computing, software optimization

February 10, 2018 by suejb.memeti

Zorua: Enhancing Programming Ease, Portability, and Performance in GPUs by Decoupling Programming Models from Resource Management

Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Khan, Ashish Shrestha, Saugata Ghose, Phillip B. Gibbons, Onur Mutlu

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Tags: Computer science, CUDA, Hardware Architecture, nVidia, Virtualization

February 10, 2018 by hgpu

Lost in Abstraction: Pitfalls of Analyzing GPUs at the Intermediate Language Level

Anthony Gutierrez, Bradford M. Beckmann, Alexandru Dutu, Joseph Gross, John Kalamatianos, Onur Kayiran, Michael LeBeane, Matthew Poremba, Brandon Potter, Sooraj Puthoor, Matthew D. Sinclair, Mark Wyse, Jieming Yin, Xianwei Zhang, Akshay Jain, Timothy G. Rogers

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Tags: ATI IL, Computer science, HSA

February 10, 2018 by hgpu

Accelerating Deep Neural Networks on Low Power Heterogeneous Architectures

Manolis Loukadakis, Jose Cano, Michael O'Boyle

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Tags: ARM, Computer science, Deep learning, Heterogeneous systems, Neural networks, OpenCL

February 10, 2018 by hgpu

Ikra-Cpp: A C++/CUDA DSL for Object-Oriented Programming with Structure-of-Arrays Layout

Matthias Springer, Hidehiko Masuhara

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Tags: Computer science, CUDA, Data Structures and Algorithms, DSL, nVidia, Package

February 9, 2018 by hgpu

Combined Spatial and Temporal Blocking for High-Performance Stencil Computation on FPGAs Using OpenCL

Hamid Reza Zohouri, Artur Podobas, Satoshi Matsuoka

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Tags: Computer science, FPGA, OpenCL, Stencil computation

February 9, 2018 by hgpu

MiMatrix: A Massively Distributed Deep Learning Framework on a Petascale High-density Heterogeneous Cluster

Xin Chen, Hua Zhou, Yuxiang Gao, Yu Zhu, Dongyan Wang

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Tags: Algorithms, Computer science, CUDA, Deep learning, GPU cluster, Heterogeneous systems, nVidia, RDMA, Tesla P100

February 9, 2018 by hgpu

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

GEAK-agent: LLM-based AI agent, which can write correct and efficient GPU kernels automatically

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks

OpenDwarfs 2025: re-engineered version of the OpenDwarfs benchmark suite, for compatibility with modern platforms

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

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