In today’s rapidly evolving life sciences sector, High-Performance Computing (HPC) is transforming the way researchers and companies approach complex problems like genomics, protein folding, and bioinformatics. During a recent PTP Lunch and Learn session, Jon Myer sat down with Aidan Sullivan, Cloud Engineer at PTP, to discuss the growing importance of HPC in the life sciences industry.
This post delves into the key insights from their conversation, outlining the benefits, challenges, and best practices for implementing HPC in the cloud, particularly through AWS solutions like ParallelCluster, Batch, and Health Omics.
What is HPC, and Why is it Important for Life Sciences?
High-Performance Computing (HPC) allows life sciences organizations to handle vast amounts of data and perform computationally expensive tasks quickly. Traditionally, HPC was associated with on-premises supercomputers in cutting-edge research institutions. However, with the cloud, HPC has evolved into a fleet of servers (nodes) that process tasks through workload managers and batch schedulers.
In the life sciences, HPC plays a crucial role in tasks such as predicting the structure of DNA, protein folding, and large-scale genomics analysis. These processes require immense computational power and would take years to complete on standard servers. By leveraging HPC in the cloud, life sciences companies can achieve faster results, accelerating research and innovation.
Key Applications of HPC in Life Sciences
Aidan explained how HPC is used by bioinformatics teams for tasks like genomics pipelines and predicting the folding structure of proteins. One of the most notable examples is the use of AlphaFold, a deep learning tool that solves one of biology’s toughest problems—accurately predicting how proteins fold into their 3D structures.
HPC enables researchers to run these highly complex computations efficiently, delivering results that would otherwise be impossible in a timely manner. Furthermore, cloud-based HPC allows teams to spin up powerful servers on-demand, providing temporary development environments for tasks like data analysis with tools such as Jupyter Notebooks.
Challenges of Implementing HPC in Life Sciences
While the benefits of HPC are vast, there are significant challenges in implementing these systems, especially in fast-paced life sciences environments. Aidan noted that the needs of these organizations often change rapidly, making it necessary to scale infrastructure quickly. The infrastructure that worked six months ago may no longer be suitable for new projects or development work.
Additionally, security is a critical concern when scaling HPC environments. It is essential to lock down HPC systems with proper security measures such as VPCs, authentication, and security groups to protect sensitive research data.
The Role of PTP in HPC Implementation
Companies looking to implement HPC often face difficulties in balancing speed, cost, and security. This is where PTP’s expertise comes into play. PTP has a wealth of experience in building and managing HPC environments, offering clients pre-built infrastructure as code and an “out-of-the-box” HPC toolkit. This helps companies avoid common pitfalls, such as overspending or neglecting security, while allowing them to focus on their core work—data analysis and research.
By partnering with PTP, life sciences organizations can benefit from pre-built infrastructure, cost management strategies, and guidance on aligning their HPC environments with best practices.
Common Pitfalls in DIY HPC Implementation
Aidan highlighted several challenges organizations face when implementing HPC on their own. One common issue is an overemphasis on the compute aspect of HPC while neglecting data governance. When working with large datasets, it’s essential to ensure that the shared storage attached to the HPC system is properly managed to avoid unnecessary data bloat, which can drive up costs.
Furthermore, poor data organization within systems like Amazon S3 can cause inefficiencies, especially when datasets are spread across multiple locations without proper naming conventions. These missteps can result in costly mistakes during HPC workloads, making it essential to establish strong data governance and workflow management before diving into HPC projects.
AWS HPC Offerings for Life Sciences
AWS offers several HPC solutions tailored specifically for life sciences, including:
- AWS ParallelCluster: An open-source tool that mimics traditional HPC environments seen in research institutions. It uses workload managers like Slurm to allocate EC2 instances for HPC jobs.
- AWS Batch: A more managed solution that abstracts much of the complexity of HPC, requiring containerized workflows and making job submission easier.
- AWS Health Omics: Designed specifically for omics data and life sciences workloads, this solution offers dedicated high-demand GPU servers but is region-locked.
Each solution has its own strengths. ParallelCluster offers more flexibility and freedom for complex, interactive HPC workloads, while Batch provides a simpler, more managed experience, ideal for containerized workflows.
Best Practices for Managing HPC Costs
Managing the cost of HPC workloads is another critical factor for life sciences organizations. Aidan shared several best practices, including establishing strong data governance to manage storage and prevent cost overruns. Setting up appropriate cost controls, such as AWS budgets and alarms, is essential to avoid unexpected bills.
Additionally, optimizing your workloads through careful planning—such as selecting the right instance types and ensuring efficient scaling—can save significant costs over time. Proper resource planning ahead of time is key to minimizing unnecessary expenses and maximizing the efficiency of your HPC environment.
Conclusion
HPC is a game-changer for life sciences companies, enabling faster, more accurate computations for genomics, protein folding, and other bioinformatics tasks. While implementing HPC comes with its own set of challenges, partnering with experienced providers like PTP ensures organizations can leverage the full power of cloud-based HPC without compromising on security, cost, or performance.
By following best practices for cost management and workload optimization, life sciences organizations can make the most of their HPC investments, accelerating their research and driving innovation in a competitive industry.
If you’re interested in learning more about HPC for life sciences and how PTP can support your organization’s cloud journey, watch the full Lunch & Learn session and Connect with PTP on Youtube 
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