The Next Platform

MPI and Scalable Distributed Machine Learning

MPI (Message Passing Interface) is the de facto standard distributed communications framework for scientific and commercial parallel distributed computing. The Intel MPI implementation is a core ...

Yihong Zou Advances Network Infrastructure Security Through Intent-Driven Verification Systems and Distributed Monitoring Architectures

An integrated intent-driven verification and distributed monitoring framework strengthens network infrastructure security by uniting real-time ...
Analytics Insight

How Great Engineering Leaders Think: Pranav Prabhakar on Data Drift, Distributed Teams, and Real-World ML

Pranav Prabhakar is an engineering leader with expertise in building scalable systems, deploying machine learning in ...
Business Wire

Quobyte First Distributed File System with TensorFlow Plug-in to Enhance Machine Learning Capabilities

SANTA CLARA, Calif.--(BUSINESS WIRE)--Quobyte® Inc., a leading developer of modern storage system software, today announced that the Quobyte Data Center File System is the first distributed file ...
insideHPC

RESEARCH: MLI – An API for Distributed Machine Learning

MLI is an Application Programming Interface (API) designed to address the challenges of building machine learning algorithms in a distributed setting based on data-centric computing. Its primary goal ...
insideHPC

Amazon SageMaker goes for “Infinitely Scalable” Machine Learning

Over at the All Things Distributed blog, Werner Vogels writes that the new Amazon SageMaker is designed for building machine learning algorithms that can handle “an infinite amount of data.” In ...
MIT Technology Review

The success of machine learning rests on scalability

Steve Roddy is Vice President, Machine Learning Group, at Arm. Change is constant, and artificial intelligence (AI) and machine learning (ML) are changing everything, all over again. For developers ...