SIAM Journal on Scientific and Statistical Computing
Hybrid Krylov methods for nonlinear systems of equations
SIAM Journal on Scientific and Statistical Computing
Towards polyalgorithmic linear system solvers for nonlinear elliptic problems
SIAM Journal on Scientific Computing
Convergence Analysis of Pseudo-Transient Continuation
SIAM Journal on Numerical Analysis
Achieving high sustained performance in an unstructured mesh CFD application
SC '99 Proceedings of the 1999 ACM/IEEE conference on Supercomputing
Evaluating derivatives: principles and techniques of algorithmic differentiation
Evaluating derivatives: principles and techniques of algorithmic differentiation
Parallel simulation of compressible flow using automatic differentiation and PETSc
Parallel Computing - Special issue on parallel computing in aerospace
A Combinatorial Scheme for Developing Efficient Composite Solvers
ICCS '02 Proceedings of the International Conference on Computational Science-Part II
Parallel components for PDEs and optimization: some issues and experiences
Parallel Computing - Special issue: Advanced environments for parallel and distributed computing
Energy optimization techniques in cluster interconnects
Proceedings of the 2003 international symposium on Low power electronics and design
Exploiting bank locality in multi-bank memories
Proceedings of the 2003 international conference on Compilers, architecture and synthesis for embedded systems
Pseudotransient Continuation and Differential-Algebraic Equations
SIAM Journal on Scientific Computing
Faster PDE-based simulations using robust composite linear solvers
Future Generation Computer Systems - Special issue: Selected numerical algorithms
Reducing Power with Performance Constraints for Parallel Sparse Applications
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 11 - Volume 12
The role of multi-method linear solvers in PDE-based simulations
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartI
| Hi-index | 0.00 |
Current trends in microprocessor design indicate that chips are approaching their packaging thermal limits, and the power-related costs of high-performance clusters and multiprocessors continue to grow as a quadratic function of peak execution rates and clock frequencies. Although a faster scientific simulation, such as one obtained by exploiting quality-performance tradeoffs, is also often one that consumes less power by using fewer compute cycles, a major challenge is developing explicitly power-aware scientific computing tools that can exploit special energy-saving features of the circuit fabric. Such tools are perhaps most natural when scientific computing involved sparse or irregular computations, for example, simulations based on partial differential equations in two or three spatial dimensions solved using implicit or semi-implicit schemes. Sparse kernels typically cannot execute near peak rates of the CPU's, and there is potential for tuning them to co-manage both power and performance characteristics. Furthermore, each sparse kernel often has a variety of implementations offering a wide range of tradeoffs in solution quality (e.g., accuracy, reliability, and scalability) and performance (e.g., execution time/rate and parallel efficiency/speedup). Consequently, proper methodselection to meet changing application quality-of-service requirements and changing technologies can potentially provide dramatic performance improvements and savings in energy by using circuit fabric features such as dynamic voltage scaling. Our goal is to design adaptive tools for sparse computations that deliver reduced-energy realizations without adversely impacting application performance. In this paper, we provide an overview of our project and discuss some initial results.