2 posts tagged with "workflow-optimization"

Amazon S3 (Simple Storage Service) is built around the concept of storing files as objects, where each file is identified by a unique key rather than a traditional file system path. While this architecture offers scalability and flexibility for storage, it can present challenges when used as a standard file system, especially in bioinformatics workflows. When running Nextflow with S3 as the input/output backend, there are trade-offs to consider—particularly when dealing with large numbers of small files. In such cases, Nextflow may spend significant time handling downloads and uploads via the AWS CLI v2, which can impact overall workflow performance.On this blog post, we will start with downloading input first. Let’s explore this in more detail.

Many bioinformatics tools provide options to adjust the number of threads or CPU cores, which can reduce execution time with a modest increase in resource cost. But does doubling computational resources always result in processes running twice as fast? In practice, the speed-up is often less than linear, and each tool behaves differently.