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Convert Massive Data Sets into Life Sciences Breakthroughs

Remove IT barriers and get faster time to results with tailored infrastructure and expert guidance

Don’t let Computing Resources or Emerging Technology Limit your Discovery

Science and technology are becoming more intertwined every day. Modern researchers must address not only biology and chemistry but also bioinformatics, genomics, big data analytics, quantitative mathematical modeling, computational bio-imaging, and high-performance computing.

However, managing and extracting useful information from the vast amounts of data being generated by modern research is not a side project. Deep domain expertise and state-of-the-art IT infrastructure is critical to developing computational models that can accurately simulate, analyze, and even predict the complex dynamics of living organisms. The right technology partner—with the right expertise to help support a broad range of end-user skill levels—is vital to success.

“After evaluating multiple cluster management products, we chose Scyld ClusterWare for the processing of large amounts of image data. Scyld ClusterWare contains a robust, easy-to-use and unique Single System Image architecture, which we believe will resonate well with researchers using the SOLiD platform for a wide variety of applications.”

Dr. Timothy Burcham – Life Technologies, Senior Director of SOLiD R&D

Key Infrastructure Issues for Life Sciences

  • High Performance Computing – Powerful but still cost-effective computing resources are critical to processing massive, inter-related data sets, a concept Penguin Computing™ helped pioneer with the Scyld Beowulf Linux computing cluster design and is embodied today in the densest turn-key Open Compute Project (OCP) cluster on the market, providing both power and the ability to operate with other open, interchangeable technologies as well as the expertise to help you design a custom computing environment that meets the needs of your current research and is set up to easily scale in the future.
  • Artificial Intelligence (AI) – AI extends traditional HPC by allowing researchers to analyze large volumes of data in situations where simulation alone cannot fully predict the real world, such as in medical imaging, bioinformatics, and drug discovery. This is often accomplished by using graphics processing unit (GPU)- accelerated computing, where GPUs handle tasks rather than central processing units (CPUs). Penguin Computing has such deep AI expertise that some of the top AI research centers in the U.S. not only buy technology but also professional and managed services to run the technology from Penguin Computing.
  • Storage – Processing massive data sets requires tremendous storage technology infrastructure, but modern budgets require agile, cost-effective solutions. Penguin Computing solves that problem with an open data center solution that includes the flexibility of Linux-based software-defined storage (SDS) in a variety of file systems so that researchers can scale as needed.
  • Networking – Software-defined networking, especially with open, interchangeable technologies, gives researchers greater flexibility and customizations. That’s why Penguin Computing offers an entire family of full-featured, managed switches with a variety of Linux software stack options.