Data Discipline: Managing Engineering Data from AI-powered Design
The advancements in the fields of AI and ML, combined with the increased availability of robust simulation, testing, and field data sets has made engineering data science a critical component of the modern product development lifecycle, but in order to extract maximum value from these exciting tools, companies need a plan to store, manage, and utilize their data efficiently. They need data discipline
How to Become an I/O Expert
Altair Breeze™ and Altair Mistral™ are I/O profiling tools that tell you how your applications are using storage. These unique products provide unrivalled insight into application dependencies and I/O patterns so system administrators and developers can troubleshoot and tune their applications. Dr. Rosemary Francis is the founder and CEO of the company that developed Breeze and Mistral, now part of Altair. She shares her experiences and describe how I/O profiling helps identify inefficiencies at the job level, optimise I/O to prep for and streamline cloud migration, and tune hybrid cloud. Altair I/O monitoring products help you understand the way applications access data to make every engineer an I/O expert. Reviewing this video on demand will help you to understand how Mistral and Breeze help design and execute complex physical design flows, reduce design risk, save money, and accelerate time-to-market by spotting critical dependencies.
Altair Mistral Demo
Mistral is the leading I/O profiling tool for high-performance computing. Mistral monitors I/O, CPU and memory, quickly locating rogue jobs and storage bottlenecks.
Product Overview Videos
Profiling I/O for Genome Pipelines: Sanger Institute Gets Fast, Agile, and Cloud-ready With Mistral and Breeze
According to Cancer Research UK, 1 in 2 people born after 1960 will get cancer at some point in their lives. Carrying out genome projects to find cures is a necessity, and the Wellcome Sanger Institute is on the front lines of genomic research.
The Institute's team needed to make one of their cancer pipelines portable and tune it for cloud deployment. They used Altair Mistral™ to profile the pipeline and look for inefficient I/O patterns and used Altair Breeze™ to profile the containerized workload in the cloud on Amazon Web Services (AWS).
EDA in the Cloud: Containerization, Migration, and System Telemetry
Cloud computing is becoming an increasingly good choice for EDA, but a data-led transformation is needed to take advantage of the flexibility that public compute resources can offer and to maximize performance and cost. Cloud allows an organization to benefit from a clear return on investment that supports innovation and rapid prototyping, provided those advantages are fully exploited. The wins achievable by a well-planned hybrid cloud strategy should see reduced costs both on-premises and in the cloud. The ability to dynamically tune compute and storage resources based on business and application needs is only available in the cloud, and only if the right telemetry and data pipelines are in place to inform infrastructure decisions.
In this paper we discuss how to put that plan in place and ensure that key business objectives are met as workflows are adapted and migrated to a new compute environment.
Profiling OpenFOAM With Altair I/O Analytics Tools on Oracle Cloud Infrastructure
The software tool OpenFOAM is used extensively in high-performance computing (HPC) to create simulations but is known to have challenging I/O patterns. To uncover the reasons why, we profiled OpenFOAM with the Altair Breeze™ and Altair Mistral™ I/O profiling tools on the Oracle bare metal cloud. The results detailed in this white paper provide a clear picture about why OpenFOAM performs slowly at times and highlight key areas for improvement.
I/O Profiling to Improve Storage Performance at Diamond Light Source on an Altair Grid Engine Cluster
Diamond Light Source is the UK’s national synchrotron or particle accelerator. It works like a giant microscope, harnessing the power of electrons to produce bright light that scientists can use to study anything from fossils to jet engines to viruses and vaccines. Because Diamond Light Source handles a wider variety of workloads than many, performance of both in-house and third-party applications is vital. The team, which employs Altair® Grid Engine® for workload management, used Altair Mistral™ to identify straightforward improvements that could be made to improve performance and cut down runtime.
Accelerating Cloud-based Genomics Pipelines Through I/O Profiling for Analysis of More Than 3,000 Whole Genome Pairs on AWS
This paper presents an overview of the work by the Wellcome Sanger Institute to make one of their cancer pipelines portable and to tune it for cloud deployment using the Altair Breeze™ and Altair Mistral™ I/O profiling tools. With the insight from the tools we were able to tune the cloud configuration to boost speed by 20% with a cost reduction of 10%.
AWS Improves Write Performance by 4X With Mistral I/O Profiling
An AWS customer wanted to scale their machine learning (ML) workload to hundreds of thousands of machine instances. Their goal was to download large images, including people and cars, from S3 to EBS storage to process for training a self-driving car. Optimizing and scaling storage usage was key, but a bottleneck was created when writing the images to disc. The AWS team profiled the application using Altair Mistral™ to see how the workflow could be improved, with results that were well worth the effort.
Planning Cloud Strategy for HPC and High-throughput Applications
When adopting flexible compute, half the challenge is in selecting a storage solution that suits the application. Whether you are tuning for performance, throughput, or cost, or a combination of all three, it’s important to balance the compute nodes with the right access to data so that you are not paying for underutilized resources.
Altair Mistral – Live HPC System Telemetry and I/O Monitoring
Altair Mistral™ is the leading application monitoring tool for HPC and scientific computing. It’s lightweight enough to run in production but flexible enough to ensure that you get the most from on-premises HPC and have the information to manage your hybrid cloud. It monitors I/O, CPU, and memory, quickly locating rogue jobs and storage bottlenecks and keeping track of what’s running on clusters day-to-day.