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Argobots: A Lightweight Low-Level Threading and Tasking Framework

IEEE transactions on parallel and distributed systems, 2018-03, Vol.29 (3), p.512-526

2018

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Micro-kernels for portable and efficient matrix multiplication in deep learning

The Journal of supercomputing, 2023-05, Vol.79 (7), p.8124-8147

2023

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A BLIS-like matrix multiplication for machine learning in the RISC-V ISA-based GAP8 processor

The Journal of supercomputing, 2022-11, Vol.78 (16), p.18051-18060

2022

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Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors

The international journal of high performance computing applications, 2024-03, Vol.38 (2), p.55-68

2024

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PyDTNN: A user-friendly and extensible framework for distributed deep learning

The Journal of supercomputing, 2021-09, Vol.77 (9), p.9971-9987

2021

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BestOf: an online implementation selector for the training and inference of deep neural networks

The Journal of supercomputing, 2022-11, Vol.78 (16), p.17543-17558

2022

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Parallel GEMM-based convolutions for deep learning on multicore ARM and RISC-V architectures

Journal of systems architecture, 2024-08, Vol.153, p.103186, Article 103186

2024

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Algorithm 1039: Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM

ACM transactions on mathematical software, 2024-03, Vol.50 (1), p.1-34, Article 6

2024

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Performance–energy trade-offs of deep learning convolution algorithms on ARM processors

The Journal of supercomputing, 2023-06, Vol.79 (9), p.9819-9836

2023

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Efficient and portable Winograd convolutions for multi-core processors

The Journal of supercomputing, 2023-07, Vol.79 (10), p.10589-10610

2023

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Parallel GEMM-based convolution for deep learning on multicore RISC-V processors

The Journal of supercomputing, 2024, Vol.80 (9), p.12623-12643

2024

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Accelerating distributed deep neural network training with pipelined MPI allreduce

Cluster computing, 2021-12, Vol.24 (4), p.3797-3813

2021

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Tackling the Matrix Multiplication Micro-Kernel Generation with Exo

2024 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), 2024, p.182-193

2024

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Automatic generation of ARM NEON micro-kernels for matrix multiplication

The Journal of supercomputing, 2024, Vol.80 (10), p.13873-13899

2024

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Using machine learning to model the training scalability of convolutional neural networks on clusters of GPUs

Computing, 2023-05, Vol.105 (5), p.915-934

2023

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Communication-Avoiding Fusion of GEMM-Based Convolutions for Deep Learning in the RISC-V GAP8 MCU

IEEE internet of things journal, 2024-11, Vol.11 (21), p.35640-35653

2024

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Reformulating the direct convolution for high-performance deep learning inference on ARM processors

Journal of systems architecture, 2023-02, Vol.135, p.102806, Article 102806

2023

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High performance and energy efficient inference for deep learning on multicore ARM processors using general optimization techniques and BLIS

Journal of systems architecture, 2022-04, Vol.125, p.102459, Article 102459

2022

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Analyzing the impact of the MPI allreduce in distributed training of convolutional neural networks

Computing, 2023-05, Vol.105 (5), p.1101-1119

2023

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On the adequacy of lightweight thread approaches for high-level parallel programming models

Future generation computer systems, 2018-07, Vol.84 (C), p.22-31

2018

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Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

The Journal of supercomputing, 2018-11, Vol.74 (11), p.5628-5642

2018

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Programming parallel dense matrix factorizations with look-ahead and OpenMP

Cluster computing, 2020-03, Vol.23 (1), p.359-375

2020

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Improving the user experience of the rCUDA remote GPU virtualization framework

Concurrency and computation, 2015-09, Vol.27 (14), p.3746-3770

2015

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A Review of Lightweight Thread Approaches for High Performance Computing

2016 IEEE International Conference on Cluster Computing (CLUSTER), 2016, p.471-480

2016

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GLTO: On the Adequacy of Lightweight Thread Approaches for OpenMP Implementations

2017 46th International Conference on Parallel Processing (ICPP), 2017, p.60-69

2017

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Argobots: A Lightweight Low-Level Threading and Tasking Framework

Micro-kernels for portable and efficient matrix multiplication in deep learning

A BLIS-like matrix multiplication for machine learning in the RISC-V ISA-based GAP8 processor

Experiences with nested parallelism in task-parallel applications using malleable BLAS on multicore processors

PyDTNN: A user-friendly and extensible framework for distributed deep learning

BestOf: an online implementation selector for the training and inference of deep neural networks

Parallel GEMM-based convolutions for deep learning on multicore ARM and RISC-V architectures

Algorithm 1039: Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM

Performance–energy trade-offs of deep learning convolution algorithms on ARM processors

Efficient and portable Winograd convolutions for multi-core processors

Parallel GEMM-based convolution for deep learning on multicore RISC-V processors

Accelerating distributed deep neural network training with pipelined MPI allreduce

Tackling the Matrix Multiplication Micro-Kernel Generation with Exo

Automatic generation of ARM NEON micro-kernels for matrix multiplication

Using machine learning to model the training scalability of convolutional neural networks on clusters of GPUs

Communication-Avoiding Fusion of GEMM-Based Convolutions for Deep Learning in the RISC-V GAP8 MCU

Reformulating the direct convolution for high-performance deep learning inference on ARM processors

High performance and energy efficient inference for deep learning on multicore ARM processors using general optimization techniques and BLIS

Analyzing the impact of the MPI allreduce in distributed training of convolutional neural networks

On the adequacy of lightweight thread approaches for high-level parallel programming models

Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models

Programming parallel dense matrix factorizations with look-ahead and OpenMP

Improving the user experience of the rCUDA remote GPU virtualization framework

A Review of Lightweight Thread Approaches for High Performance Computing

GLTO: On the Adequacy of Lightweight Thread Approaches for OpenMP Implementations

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