May 27, 2019 · In this work, we introduce a new, simple yet theoretically and practically effective compression technique: natural compression (NC). Our ...

Abstract. Modern deep learning models are often trained in parallel over a collection of distributed machines to reduce training time.

This work introduces a new, simple yet theoretically and practically effective compression technique: em natural compression (NC), which is applied ...

Modern deep learning models are often trained in parallel over a collection of distributed machines to reduce training time. In such settings, communication.

NC is “natural” since the nearest power of two of a real expressed as a float can be obtained without any computation, simply by ignoring the mantissa.

Introduction. Distributed machine learning has become common practice, given the increasing model complexity and the sheer size of real-world datasets.

Communication compression is an effective method to alleviate communication overhead, and it has evolved from simple random sparsification or quantization to ...

Sep 5, 2022 · The combined compression technique re- duces the number of communication rounds without any noticeable impact on convergence providing the same ...

We now introduce three classes of biased compressors, the first two are new, which can be seen as natural extensions of unbiased compressors. †(2) can be also ...

We introduce Tensor Homomorphic Compression (THC), a novel bi-directional compression framework that enables the direct aggregation of compressed values.