In the biotech and life sciences sectors, data processing speed can make or break research timelines. That’s where high-performance computing (HPC) comes in—enabling organizations to accelerate scientific discovery through scalable compute clusters and automated pipelines. In a recent podcast hosted by Jon Myer, PTP’s CloudOps Lead Architect Micah Frederick shared how PTP helps clients harness cloud-based HPC for faster, more secure outcomes with managed IT services for life sciences.
What Is High-Performance Clustering?
High-performance clustering refers to running complex workflows across many compute nodes simultaneously. This is especially useful in genomics, bioinformatics, and regulated research where processing pipelines can span days—or even weeks—without parallelization.
PTP’s CloudOps team builds, deploys, and automates these clusters using AWS EC2, Amazon S3, and tools like Nextflow—helping researchers reduce processing time from days to hours.
Bridging the Academic-to-Industry HPC Gap
Many researchers are used to academic HPC clusters but struggle to replicate those resources in commercial life sciences settings. PTP bridges that gap by architecting cloud-ready HPC environments for biotech startups and research organizations—ensuring speed, flexibility, and compliance.
Automation for Scientific Workflows
Automation is key to making HPC scalable and sustainable. PTP enables automated cluster spin-up and shutdown, dynamic parallelization, and cost controls that reduce waste and accelerate results. This strategy supports faster research pipelines without overburdening IT teams.
Reducing HPC Costs Without Performance Trade-offs
- Run large clusters for short durations
- Use AWS spot instances to reduce hourly rates
- Automate shutdowns post-execution to eliminate idle time
These practices give life sciences teams the ability to scale for peak workloads—then scale down cost-efficiently.
Secure Infrastructure for Regulated Environments
For organizations operating under HIPAA, GxP, or similar frameworks, security is non-negotiable. PTP implements encryption, access control, and ephemeral environments to isolate sensitive data and reduce exposure.
Enabling Self-Sufficient Research Teams
PTP doesn’t just deliver managed services—it educates clients and empowers their teams. From pipeline architecture to optimization strategies, PTP ensures researchers and data engineers can operate with speed, security, and confidence.
A Look Ahead
As life sciences research evolves, PTP continues to refine its HPC services to support emerging use cases like protein modeling, multi-omics analysis, and machine learning integration. Whether you're migrating workloads or building new cloud-native pipelines, PTP is your partner for scientific computing success.
🔎 Transcript Highlights: High-Performance Clustering with PTP
00:00 – Host Jon Myer welcomes Micah Frederick from PTP
02:59 – What is HPC? How PTP bridges gaps for life sciences teams
05:18 – When biotech teams need pipeline optimization
07:15 – Migrating from academic clusters to AWS infrastructure
11:18 – Automating Nextflow pipelines for scientific research
16:00 – Cost control via automation and ephemeral compute
21:18 – Leveraging AWS spot instances to optimize spend
27:58 – Using AWS Storage Gateway for lab data ingestion
34:11 – Self-service workflows with GitHub and CodeCommit
37:32 – How PTP enforces secure, zero-persistence compute
42:58 – Final thoughts: accelerating secure research with HPC
Connect with PTP
If you’re interested in learning more about PTP’s approach to high-performance clustering and automation, be sure to connect with them. Their expertise can help you navigate the complexities of HPC and achieve your business objectives with confidence.