Appears in ACM Transactions on Computer Systems,19(2):111-170, May 2001.
Angela Demke Brown, Todd C. Mowry and Orran Krieger
School of Computer Science
Carnegie Mellon University
Pittsburgh, PA 15213
Current operating systems offer poor performance when a numeric application’s working set does not fit in main memory. As a result, programmers who wish to solve "out-of-core" problems efficiently are typically faced with the onerous task of rewriting an application to use explicit I/O operations (e.g., read/write). In this paper, we propose and evaluate a fully automatic technique which liberates the programmer from this task, provides high performance, and requires only minimal changes to current operating systems. In our scheme the compiler provides the crucial information on future access patterns without burdening the programmer; the operating system supports nonbinding prefetch and release hints for managing I/O; and the operating system cooperates with a run-time layer to accelerate performance by adapting to dynamic behavior and minimizing prefetch overhead. This approach maintains the abstraction of unlimited virtual memory for the programmer, gives the compiler the flexibility to aggressively insert prefetches ahead of references, and gives the operating system the flexibility to arbitrate between the competing resource demands of multiple applications. We implemented our compiler analysis within the SUIF compiler, and used it to target implementations of our run-time and OS support on both research and commercial systems (Hurricane and IRIX 6.5, respectively). Our experimental results show large performance gains for out-of-core scientific applications on both systems: more than 50% of the I/O stall time has been eliminated in most cases, thus translating into overall speedups of roughly twofold in many cases.
FULL PAPER: pdf / postscript