A scalable approach based on deep learning for big data time series forecasting
JF Torres, A Galicia, A Troncoso… - Integrated Computer …, 2018 - content.iospress.com
This paper presents a method based on deep learning to deal with big data times series
forecasting. The deep feed forward neural network provided by the H2O big data analysis …
forecasting. The deep feed forward neural network provided by the H2O big data analysis …
Shuffle net: An application of generalized perfect shuffles to multihop lightwave networks
MG Hluchyj, MJ Karol - Journal of Lightwave Technology, 1991 - ieeexplore.ieee.org
A multihop wavelength-division multiplexing (WDM) approach, referred to as Shuffle Net, for
achieving concurrency in distributed lightwave networks is proposed. A Shuffle Net can be …
achieving concurrency in distributed lightwave networks is proposed. A Shuffle Net can be …
{FpgaNIC}: An {FPGA-based} versatile 100gb {SmartNIC} for {GPUs}
Given that the increasing rate of network bandwidth is far ahead of that of the compute
capacity of host CPU, which by default processes network packets, SmartNIC has been …
capacity of host CPU, which by default processes network packets, SmartNIC has been …
GPU-aware MPI on RDMA-enabled clusters: Design, implementation and evaluation
Designing high-performance and scalable applications on GPU clusters requires tackling
several challenges. The key challenge is the separate host memory and device memory …
several challenges. The key challenge is the separate host memory and device memory …
Efficient large message broadcast using NCCL and CUDA-aware MPI for deep learning
Emerging paradigms like High Performance Data Analytics (HPDA) and Deep Learning (DL)
pose at least two new design challenges for existing MPI runtimes. First, these paradigms …
pose at least two new design challenges for existing MPI runtimes. First, these paradigms …
Designing efficient small message transfer mechanism for inter-node MPI communication on InfiniBand GPU clusters
Increasing number of MPI applications are being ported to take advantage of the compute
power offered by GPUs. Data movement on GPU clusters continues to be the major …
power offered by GPUs. Data movement on GPU clusters continues to be the major …
Adaptive and hierarchical large message all-to-all communication algorithms for large-scale dense gpu systems
In recent years, GPU-enhanced clusters have become more prevalent in High-Performance
Computing (HPC), leading to a demand for more efficient multi-GPU communication. This …
Computing (HPC), leading to a demand for more efficient multi-GPU communication. This …
Exploring gpu-to-gpu communication: Insights into supercomputer interconnects
D De Sensi, L Pichetti, F Vella… - … Conference for High …, 2024 - ieeexplore.ieee.org
Multi-GPU nodes are increasingly common in the rapidly evolving landscape of exascale
supercomputers. On these systems, GPUs on the same node are connected through …
supercomputers. On these systems, GPUs on the same node are connected through …
Performance evaluation of MPI libraries on GPU-enabled OpenPOWER architectures: Early experiences
Abstract The advent of Graphics Processing Unit (GPU)-enabled OpenPOWER architectures
are empowering the advancement of various High-Performance Computing (HPC) …
are empowering the advancement of various High-Performance Computing (HPC) …
Efficient process arrival pattern aware collective communication for deep learning
P Alizadeh, A Sojoodi, Y Hassan Temucin… - Proceedings of the 29th …, 2022 - dl.acm.org
MPI collective communication operations are used extensively in parallel applications. As
such, researchers have been investigating how to improve their performance and scalability …
such, researchers have been investigating how to improve their performance and scalability …