Growing HPC Utilization for Life Sciences with Remote Visualization

In order to drive the next medical discovery, IT leaders are looking to the latest innovations to ensure optimal efficiency, productivity, and performance. For life sciences organizations, speed and accuracy are integral to success.

Over the past decade, compute research and development has had an enormous impact on the life sciences industry. Researchers are now using high performance computing (HPC) technologies to quickly visualize, collaborate, and analyze research data in order to accelerate time to insight, reduce operational costs, and enhance the drug research process.


Prior to the digital age, drug discovery and implementation involved a costly and time-consuming process of collecting, assaying, and analyzing countless outcomes and variables. Today, HPC solutions for life sciences are helping to improve the collaboration, speed and accuracy of drug discovery by leveraging a combination of modeling, simulation, and big data analytics.

These technological advancements in applying HPC to Life Sciences are helping research institutions dramatically expand their R&D and/or product development. As with other use cases, initial computing has been done with individually deployed workstations and departmental HPC clusters where increasing personal productivity, organizational efficiency and overall productivity suffered through the need to maintain disparate, dispersed, and often ill-deployed systems. The goal is to streamline drug testing and delivery, and speed time to market through improved workplace productivity and IT efficiency.

Enter remote visualization. For use cases, such as drug research, that require user interactive graphics and input, remote visualization technology enables an organization to effectively collocate their compute resources in a data center, either on-premises or off-premises. In doing so, less capital expenditure is needed to support research workloads and, through central deployment, operational expenses are also reduced. Centralizing enables common architecture deployment, aggregated buying power, and much greater ease of service and provisioning. Additionally, the operational model increases availability as systems are typically in a more controlled environment, both for conditioned power and environment as well as for limited access and availability to inadvertently affect a system’s operability. Further, for drug discovery use cases, large data sets and comparative databases can be more efficiently affected, accessed, and maintained in a centralized environment, as well as shared collaboratively via remote visualization. It is a win-win all the way for the engineers, both remote and local, the institution’s budget, and the IT support.

Life sciences organizations can improve their IT environments significantly with remote visualization solutions:

  • Security: Remote visualization allows researchers to keep their critical data within the data center, transferring only pixels of images over the network, thus making it much harder for data intruders to gain access to sensitive data and IP.
  • Productivity: Remote visualization drives increased productivity by permitting anytime, anywhere access to graphics-intensive models and data. This increases collaboration and sharing of ideas. Time spent moving data between remote workstations and the data center is eliminated, allowing researchers to harness and share medical insights in real-time.
  • Manageability: As life sciences organizations adopt remote visualization tools, IT departments can dramatically simplify their costs and maintenance efforts. This allocates resources to business-critical operations such as load-balancing, enhanced monitoring capabilities, and greater control and management of applications.
  • Optimal resource utilization: Virtual desktop environments with embedded GPUs allow IT to provide flexible and scalable resources with greater utilization efficiency, reduced capital costs, and reduced operational costs, all the while making the drug research simulations more available and accessible, whether local or around the world.
  • Expanded application access: Highly skilled professionals value a work-life balance, and the ability to work from disparate locations on a variety of connected devices allows research institutions to retain their key scientists and engineers by providing a flexible and constantly accessible work environment.


Many research organizations are leveraging massively parallel GPU accelerators for both computational simulation and data analysis tasks. GPU computing works to speed up critical life sciences applications and data workloads, enabling researchers to conduct drug research simulations and derive actionable insight in real time.

For their massively parallel processing applications, many organizations are investing in leading-edge HPC servers with GPUs that are designed to accelerate workload performance. These powerful compute platforms deliver the scalability and flexibility needed to power increasingly complex simulations. With unmatched HPC performance, drug research has never been more efficient.

Leading-edge solutions are a critical function in increasing the efficiency and effectiveness of an organization’s HPC computational capacity, availability, and agility. Together, Hewlett Packard Enterprise (HPE) and NVIDIA are empowering organizations to innovate quickly and cost-effectively by harnessing the power of high performance remote visualization.

To learn more about how remote visualization is transforming the life sciences industry, I invite you to follow me on Twitter at @VineethRam. You can also check out @HPE_HPC and @NVIDIAAI for the latest news and updates on HPC visualization solutions.

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