Nicholas Malaya, Fellow, High-Performance Computing, AMD.

Notably, there are exciting developments within the healthcare industry where HPCs can be used to identify new treatments for diseases, specifically Alzheimer’s and cardiovascular diseases:

  • The University of California is currently using an HPC system powered by AMD to better understand the root cause of Alzheimer’s disease. By running simulations to derive the first-ever mechanistic insights, the team is now able to uncover pathways to better control thought, language, and memory.
  • The University of Utah uses the same compute system at SDSC’s Expanse centre to model a treatment for atherosclerosis, a major cause of human cardiovascular disease. Breakthroughs in this area of science could help millions of people around the world mitigate the impact of diseases that are often fatal.

NM: The capabilities of HPC systems have expanded into a broader range of applications over the past few years. We now have more processing power and memory than ever before to solve more complex problems.

  • Machine learning (ML). HPC systems provide the necessary computing power for highly advanced ML to analyze and validate vast amounts of data. One specific use case is the use of HPC for cancer research to detect melanoma in photos.
  • Big data analytics. Rapid comparison and correlation of massive data sets are used to supplement research and solve problems in academic, scientific, finance, business, health, cybersecurity, and government applications. This work requires massive throughput and compute capabilities.
  • Advanced modeling and simulation: Without having to do a physical prototype in early stages, advanced modeling and simulation allow companies to save time, materials, and staffing costs in bringing innovative products to market faster. HPC modeling and simulation are used for drug discovery and testing, energy-efficient designs for automotive and aerospace, prediction of extreme climate/weather systems, and advanced materials and energy applications.