Journal of Parallel Distributed Computing, 2003
The exploitation of idle cycles on pervasive desktop PC systems offers the opportunity to increase the available computing power by orders of magnitude (10x - 1000x). However, for desktop PC distributed computing to be widely accepted within the enterprise, the systems must achieve high levels of efficiency, robustness, security, scalability, manageability, unobtrusiveness, and openness/ease of application integration.
We describe the Entropia distributed computing system as a case study, detailing its internal architecture and philosophy in attacking these key problems. Key aspects of the Entropia system include the use of: 1) binary sandboxing technology for security and unobtrusiveness, 2) a layered architecture for efficiency, robustness, scalability and manageability, and 3) an open integration model to allow applications from many sources to be incorporated.
Typical applications for the Entropia System includes molecular docking, sequence analysis, chemical structure modeling, and risk management. The applications come from a diverse set of domains including virtual screening for drug discovery, genomics for drug targeting, material property prediction, and portfolio management. In all cases, these applications scale to many thousands of nodes and have no dependences between tasks. We present representative performance results from several applications that illustrate the high performance, linear scaling, and overall capability presented by the Entropia system.