AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters
AIgean: An Open Framework for Machine Learning on Heterogeneous Clusters
复制标题
AIgean：异构集群机器学习的开放框架
DOI：
10.1109/fccm48280.2020.00072
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Chow, Paul
中科院分区：
文献类型：
--
作者：
Tarafdar, Naif;Guglielmo, Giuseppe Di;Harris, Philip C;Krupa, Jeffrey D;Loncar, Vladimir;Rankin, Dylan S;Tran, Nhan;Wu, Zhenbin;Shen, Qianfeng;Chow, Paul
摘要机器学习（ML）在过去的十年中一直是计算界最热门的研究课题之一。对计算领域的兴趣跨越计算堆栈的所有级别。我们在图1中展示了这个堆栈。这项工作引入了一个名为Aigean的开放框架，用于在异构设备（CPU和FPGA）集群上构建和部署机器学习（ML）算法。用户可以灵活地修改图1中机器学习堆栈的任何层，以满足他们的需求。这使得机器学习领域专家可以专注于更高的算法层，而分布式系统专家可以创建下面的通信层。
Abstract Machine learning (ML) in the past decade has been one of the most popular topics of research within the computing community. Interest within the computing field ranges across all levels of the computation stack. We show this stack in Figure 1. This work introduces an open framework, called AIgean, to build and deploy machine learning (ML) algorithms on a heterogeneous cluster of devices (CPUs and FPGAs). Users can flexibly modify any layer of the machine learning stack in Figure 1 to suit their need. This allows both machine learning domain experts to focus on higher algorithmic layers, and distributed systems experts to create the communication layers below.
Galapagos：云中 FPGA 集成的全栈方法
影响因子：
3.6
作者：
Naif Tarafdar;Nariman Eskandari;Varun Sharma;Charles Lo;P. Chow
通讯作者：
P. Chow