True 3-D displays for avionics and mission crewstations
Elizabeth A. Sholler, Frederick M. Meyer, et al.
SPIE AeroSense 1997
Future high-performance virtual machines will improve performance through sophisticated online feedback-directed optimizations. This paper presents the architecture of the Jalapeño Adaptive Optimization System, a system to support leading-edge virtual machine technology and enable ongoing research on online feedback-directed optimizations. We describe the extensible system architecture, based on a federation of threads with asynchronous communication. We present an implementation of the general architecture that supports adaptive multi-level optimization based purely on statistical sampling. We empirically demonstrate that this profiling technique has low overhead and can improve startup and steady-state performance, even without the presence of online feedback-directed optimizations. The paper also describes and evaluates an online feedback-directed in- lining optimization based on statistical edge sampling. The system is written completely in Java, applying the described techniques not only to application code and standard libraries, but also to the virtual machine itself. © 2000 ACM.
Elizabeth A. Sholler, Frederick M. Meyer, et al.
SPIE AeroSense 1997
Ruixiong Tian, Zhe Xiang, et al.
Qinghua Daxue Xuebao/Journal of Tsinghua University
Charles H. Bennett, Aram W. Harrow, et al.
IEEE Trans. Inf. Theory
Chidanand Apté, Fred Damerau, et al.
ACM Transactions on Information Systems (TOIS)