Sign up for our newsletter and get the latest HPC news and analysis.
Send me information from insideHPC:


Video: HPC Reservoir Simulations on AWS with NICE

In this video, Scott Harrison from Rock Flow Dynamics and Bruno Franzini from NICE Software explain how they scale HPC workloads in the cloud. “You’ll learn how they leverage Amazon EC2 Spot instances and Amazon S3 to create cost-effective, scalable clusters that power tNavigator, Rock Flow Dynamics’ solution for running dynamic reservoir simulations. You’ll also see how they use NICE Software’s DCV to stream the OpenGL-based user interface to interact with 3D models.”

Microsoft Acquires Cycle Computing

Today Microsoft announced it has acquired Cycle Computing, a software company focused on making cloud computing resources more readily available for HPC workloads. “Now supporting InfiniBand and accelerated GPU computing, Microsoft Azure looks to be a perfect home for Cycle Computing, which started its journey with software for aggregating compute resources at AWS. The company later added similar capabilities for Azure and Google Cloud.”

MIT Professor Runs Record Google Compute Engine job with 220K Cores

Over at the Google Blog, Alex Barrett writes that an MIT math professor recently broke the record for the largest-ever Compute Engine cluster, with 220,000 cores on Preemptible VMs. According to Google, this is the largest known HPC cluster to ever run in the public cloud.

NICE Software Releases EnginFrame 2017

“Since the NICE acquisition by Amazon Web Services (AWS), many customers asked us how to make the HPC experience in the Cloud as simple as the one they have on premises, while still leveraging the elasticity and flexibility that it provides. While we stay committed to delivering new and improved capabilities for on-premises deployments, like the new support for Citrix XenDesktop and the new HTML5 file transfer widgets, EnginFrame 2017 is our first step into making HPC easier to deploy and use in AWS, even without an in-depth knowledge of its APIs and rich service offering.”

Interview: XTREME DESIGN Automates HPC Cloud Configurations

Tokyo-based Startup XTREME DESIGN recently announced it has raised $700K of funding in its pre-series A round. Launched in early 2015, the Startup’s XTREME DNA software automates the process of configuring, deploying, and monitoring virtual supercomputers on public clouds. To learn more, we caught up with the company’s founder, Naoki Shibata.

Job of the Week: HPC Software Development Engineer at AWS

“The Amazon Web Services High Performance Computing (HPC) team is looking for Software Development Engineers (SDEs) to help drive the development of new features, functionality, and capabilities for AWS Batch. AWS Batch is developed by a newly formed team building a core set of offerings that allow our customers to plan, schedule, and execute batch computing workloads across the full range of AWS compute services and capabilities.”

Adrian Cockcroft Presents: Shrinking Microservices to Functions

In this fascinating talk, Cockcroft describes how hardware networking has reshaped how services like Machine Learning are being developed rapidly in the cloud with AWS Lamda. “We’ve seen the same service oriented architecture principles track advancements in technology from the coarse grain services of SOA a decade ago, through microservices that are usually scoped to a more fine grain single area of responsibility, and now functions as a service, serverless architectures where each function is a separately deployed and invoked unit.”

ANSYS Enterprise Cloud goes with Cycle Computing for HPC

“Our collaboration with Cycle Computing enables the ANSYS Enterprise Cloud to meet the elastic capacity and security requirements of enterprise customers,” said Ray Milhem, vice president, Enterprise Solutions and Cloud, ANSYS. “CycleCloud has run some of the largest Cloud Big Compute and Cloud HPC projects in the world, and we are excited to bring their associated, proven software capability to our global customers with the ANSYS Enterprise Cloud.”

CUDA Made Easy: An Introduction

“CUDA C++ is just one of the ways you can create massively parallel applications with CUDA. It lets you use the powerful C++ programming language to develop high performance algorithms accelerated by thousands of parallel threads running on GPUs. Many developers have accelerated their computation- and bandwidth-hungry applications this way, including the libraries and frameworks that underpin the ongoing revolution in artificial intelligence known as Deep Learning.”

New Site Lists all Comparable Features from AWS, Azure, and Google Cloud

Are you shopping for Public Cloud services? A new Public Cloud Services Comparison site gives a service & feature level mapping between the 3 major public clouds: Amazon Web Service, Microsoft Azure & Google Cloud. Published by Ilyas F, a Cloud Solution Architect at Xebia Group, the Public Cloud Services Comparison is a handy reference manual to help anyone to quickly learn the alternate features & services between clouds.