scholar.google.com › citations
Implementing ML on distributed memory multiprocessors. Authors: Peter Bailey ... Index Terms. Implementing ML on distributed memory multiprocessors.
The advent of distributed memory multicomputers, such as the Fujitsu AP1000, enables the imple- mentation of parallel programming languages where every�...
The CAP ML project seeks to develop a version of ML that is suitable for use on a distributed memory multiprocessor architecture such as the Fujitsu AP1000.
Parallel distributed memory multiprocessing will be the way to cope with many of these large computing problems. This paper will touch on some of the most�...
Abstract. This paper describes the design of paraML, an extension of ML with primitives for par- allelism that is suitable for use on a distributed memory�...
This paper discusses a concurrency mechanism which has been implemented in the Poly/ML implementation of Standard ML and has been used on uniprocessors and�...
Jun 22, 2020 � As per the distributed training tutorial, it seems that each process will load the pre-processed data separately and then send it to GPU for training.
Missing: Implementing | Show results with:Implementing
In this paper, it is investigated simulating/implementing a fully connected multilayered feedforward neural network using the backpropagation learning�...
In this paper, as our main contribution, we propose a parallel clustering al- gorithm on distributed memory multiprocessors, that is, on a shared-nothing�...
In this paper, we present a parallel simulation of a fully connected multilayered neural network using the backpropagation learning algorithm on a distributed-�...
People also ask
What is a distributed memory multiprocessor?
What is the distributed memory model of parallel?