Category: AWS Batch

AWS partners with providers of innovative solutions such as MemVerge, an AWS Partner Network (APN) Advanced Technology Partner, whose Memory Machine Batch (MMBatch) technology complements AWS Batch by providing advanced checkpointing capabilities for EC2 Spot Instances. In this post, we look at how MemVerge’s technology can overcome the challenges of interrupted pipelines by enabling pipelines that were interrupted mid task to start from where they left off, regardless of Spot Instance reclaims. We’ll also show how MemVerge’s Batch Viewer and proven best practices empower researchers to visualize their workloads, identify bottlenecks, and apply smart strategies that make their pipelines more efficient, resilient, and cloud-optimized.

In this post, we explore how Amazon Web Services (AWS) cloud-based technologies can be used to address diversified and dynamic water challenges in Europe, the Middle East, and Africa. As climate change and demographic shifts continue to strain water resources, the need for innovative, technology-driven solutions has never been more urgent.

Computational biology is undergoing a revolution. However, the analysis of single cells is a hard problem to solve. Standard statistical techniques used in genomic analysis fail to capture the complexity present in single-cell datasets. Open Problems in Single-Cell Analysis is a community-driven effort using AWS to drive the development of novel methods that leverage the power of single-cell data.

Scientists at NC State University’s North Carolina Institute for Climate Studies (NCICS) work with large datasets and complex computational analysis. Traditionally, they did their work using on-premises computational resources. As different projects were stretching the limits of those systems, NCICS decided to explore cloud computing. As part of the Amazon Sustainability Data Initiative, we invited Jessica Mathews, Jared Rennie, and Tom Maycock to share what they learned from using AWS for climate research. As they considered exploring the cloud to support their work, the idea of leaving the comfort of the local environment was a bit scary. And they had questions: How much will it cost? What does it take to deploy processing to the cloud? Will it be faster? Will the results match what they were getting with their own systems? Here is their story and what they learned.