Understanding the Productivity Gridlock in Scientific Computing (And can Software Engineering and Computer Science Help?)

July 1, 2008
Larry Votta | Independent

The accumulated technologies and practices of general computer science and software engineering have failed to impact the productivity gridlock in scientific programming. Resolving this “productivity crisis” will require that the scientific programming communities relax their unending pursuit of 100% resource utilization and that the computer science and software engineering communities understand and appreciate the difference in goals between the two domains. Lessons learned from the great strides in general computing can then be adapted to scientific computing.

Speaker Details

Larry is a consultant for software fault tolerance and productivity. He received his B.S. degree in Physics from the University of Maryland, College Park, Maryland in 1973, and his Ph.D. degree in Physics from the Massachusetts Institute of Technology, Cambridge, Massachusetts, in 1979. He spent the next 22 years building and investigating the maintenance and evolution of network and switching software at AT&T Bell Labs and Motorola. Larry joined Sun Microsystems as a Distinguished Engineer in December 2001, working to improve the software and system reliability and availability of Sun’s products while pursuing his research interest in high availability computing and empirical software engineering. He was one of Sun Microsystems’ four principle investigators for the DARPA High Productivity Computing System (HPCS) initiative and led the Productivity analysis team. He has authored more than 60 papers and chapters of 2 books in Software Engineering. He is a member of the ACM and a Senior Member of the IEEE.