Welcome to the Global Computing Lab

The Global Computing Lab (GCLab), headed by Dr. Michela Taufer, targets large-scale, heterogeneous computer systems and their application to the sciences.

Our research focuses on the exploration, design, and implementation of alternative, more efficient computational paradigms as well as adaptive methods and user-friendly tools for large-scale simulations on grid and volunteer computing platforms.

Our main challenges are:

  1. The ability to model biological systems with computational algorithms that dynamically adapt to simulation results and simulation performance collected at runtime;
  2. The ability to assure that these simulation algorithms can, indeed, be executed in the "required" amount of time using large numbers of heterogeneous computers.

The first point refers to the adaptive calibration of prediction models based on the complexity and characteristics of the biological systems as well as the availability of computational resources. The latter point refers to having the necessary computational resources (CPU cycles, memory, network, etc.) and being able to trust the simulations results returned. Validation techniques are a key component to quantify accuracy and reliability of computational results based on the availability of experimental data as well as to identify when computing errors due to e.g., hardware malfunctions, incorrect software modifications, and malicious attacks affect prediction results.