In this paper, we develop a framework of quantized, decentralized training and propose two different strategies, which we call {\em extrapolation compression} ...
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Mar 17, 2018 · In this paper, we develop a framework of compressed, decentralized training and propose two different strategies, which we call {\em ...
To reduce the communication cost, a straightforward idea is to compress the information exchanged within the decentralized network just like centralized ...
In this paper, we develop a framework of compressed, decentralized training and propose two different strategies, which we call extrapolation compression and ...
In this paper, we develop a framework of compressed, decentralized training and propose two different strategies, which we call {\em extrapolation compression} ...
May 8, 2022 · In this work, we propose the novel framework of the compression methods for the ECL, called the Communication Compressed ECL (C-ECL).
This paper develops a framework of quantized, decentralized training and proposes two different strategies, which are called extrapolation compression and ...
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We introduce a simple algorithm that directly compresses the model differences between neighboring workers using low-rank linear compressors.
NeurIPS 2022: Overcoming communication bottlenecks for ...
www.together.ai › blog › neurips-2022-o...
Nov 30, 2022 · The key bottleneck is network bandwidth due to the high volume of communication between GPUs during training.
This paper deals with combining quantization with decentralized SGD in order to design algorithms which work well in networks with both high latency and low ...