This paper presents an empirical methodology for low power driven complex DSP embedded systems design. Unlike DSP design for high performance, research of low power DSP design has received little attention, yet power ...
详细信息
This paper presents an empirical methodology for low power driven complex DSP embedded systems design. Unlike DSP design for high performance, research of low power DSP design has received little attention, yet power dissipation is an increasingly important and growing problem. Highly accurate power prediction models for DSP software are derived. Unlike previous techniques, the methodology derives software power prediction models using statistical optimization and it is verified with real power measurements. The approach is general enough to be applied to any embedded DSP processor. Results from two different DSP processors and over 180 power measurements of DSP code show that power can be predicted far embedded systems design with less than 4% error. This result is important for developing a general methodology for power characterization of embedded DSP software since low power is critical to complex DSP applications in many cost sensitive markets.
Assessing the reliability of a software system has always been an elusive target. A program may work very well for a number of years and this same program may suddenly become quite unreliable if its mission is changed...
详细信息
Assessing the reliability of a software system has always been an elusive target. A program may work very well for a number of years and this same program may suddenly become quite unreliable if its mission is changed by the user. This has led to the conclusion that the failure of a software system is dependent only on what the software is currently doing. If a program is always executing a set of fault free modules, it will certainly execute indefinitely without any likelihood of failure. A program may execute a sequence of fault prone modules and still not fail. In this particular case, the faults may lie in a region of the code that is not likely to be expressed during the execution of that module. A failure event can only occur when the software system executes a module that contains faults. If an execution pattern that drives the program into a module that contains faults is ever selected, then the program will never fail. Alternatively, a program may execute successfully a module that contains faults just as long as the faults are in code subsets that are not executed. The reliability of the system then, can only be determined with respect to what the software is currently doing. Future reliability predictions will be bound in their precision by the degree of understanding of future execution patterns. We investigate a model that represents the program sequential execution of nodules as a stochastic process. By analyzing the transitions between modules and their failure counts, we may learn exactly where the system is fragile and under which execution patterns a certain level of reliability can be guaranteed.
In this paper we describe Snuffle, anew measurement tool for capturing, displaying and analyzing the operation of the Internet protocol stack within end-systems. Snuffle is a set of modules operating in a distributed ...
详细信息
ISBN:
(纸本)3540649492
In this paper we describe Snuffle, anew measurement tool for capturing, displaying and analyzing the operation of the Internet protocol stack within end-systems. Snuffle is a set of modules operating in a distributed fashion and supporting an on-line analysis of network and protocol performance. This kind of tool is especially suited for wireless networks.
暂无评论