Results 61 to 70 of about 4,462 (194)
TensorFlow is a popular emerging open-source programming framework supporting the execution of distributed applications on heterogeneous hardware. While TensorFlow has been initially designed for developing Machine Learning (ML) applications, in fact ...
Bulatov, Yaroslav +5 more
core +1 more source
Toward a new linpack‐like benchmark for heterogeneous computing resources
Summary This work describes some first efforts to design a new Linpack‐like benchmark useful to evaluate the performance of Heterogeneous Computing Resources. The benchmark is based on the Schur Complement reformulation of the solution of a linear equation system.
Luisa Carracciuolo +2 more
wiley +1 more source
GPU peer-to-peer techniques applied to a cluster interconnect
Modern GPUs support special protocols to exchange data directly across the PCI Express bus. While these protocols could be used to reduce GPU data transmission times, basically by avoiding staging to host memory, they require specific hardware features ...
Ammendola, Roberto +13 more
core +1 more source
TensorFlow has been the most widely adopted Machine/Deep Learning framework. However, little exists in the literature that provides a thorough understanding of the capabilities which TensorFlow offers for the distributed training of large ML/DL models ...
Awan, Ammar Ahmad +4 more
core +1 more source
Detection of Biomarkers through Functionalized Polymers
The incorporation of functional groups into polymer‐based materials such as hydrogels, nanosheets, and nanopores has revolutionized the field of biomarker detection. This comprehensive review explores the latest advancements in materials and techniques employed for polymer functionalization.
Litzy L. García‐Faustino +3 more
wiley +1 more source
Optimizing distributed systems with remote direct memory access
Fast network devices with RDMA support have been price-compatible with traditional network primitives such as Ethernet,and it’s now widely deployed in modern data centers.RDMA can be used in two ways.Firstly,it can optimize the messaging primitive in ...
Xingda WEI, Rong CHEN, Haibo CHEN
doaj
In the context of the rapid development of edge computing, optimizing data transmission and reducing latency is crucial for efficient collaborative processing among edge servers.
Donglei Xiao +3 more
doaj +1 more source
Rate-adaptive RDMA congestion control for AI clusters
The rapid growth of AI models has imposed increasingly stringent performance demands on data centers. Modern data centers adopt Remote Direct Memory Access (RDMA) to reduce CPU overhead and network latency. RDMA operates over a lossless network, and RDMA
Xin He +5 more
doaj +1 more source
This paper conducts a comprehensive survey and analysis of interconnection buses for space applications both domestically and internationally in recent years. In response to the future demands of satellites for high-performance computing, high-efficiency
Wenjie Zhao +16 more
doaj +1 more source
Design and implementation of an RDMA-based data transmission system prototype for ETF
Data transmission is crucial in nuclear physics experiments. As the size of detectors and measurement data increases, traditional Ethernet protocols have become insufficient for performance requirements.
Yuqiao Zhang +8 more
doaj +1 more source

