Abstract
Certain high-performance applications like multimedia and gaming have performance requirements beyond reducing program execution time. These applications have repetitive components whose desired performance characteristics are more naturally expressed using soft real-time theory with its probabilistic guarantees. However, for large complex gaming and multimedia applications, programmers typically avoid real-time constructs as they significantly constrain how the programmer can express functionality. Instead, such applications are developed as monolithic programs using conventional languages like C/C++. Here the soft real-time behavior of the application becomes an emergent quality rather than being enforced by design. Programmers must then tweak parameters/algorithms until the application’s soft real-time behavior becomes acceptable. There are currently no analysis techniques that directly extract the soft real-time execution characteristics of monolithic applications written without the use of real-time constructs. We introduce a domain-agnostic profiling methodology that identifies program execution-contexts whose variant behavior most significantly affects the soft real-time characteristics of the application.
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Kumar, T., Cledat, R., Sreeram, J., Pande, S. (2008). Statistically Analyzing Execution Variance for Soft Real-Time Applications. In: Amaral, J.N. (eds) Languages and Compilers for Parallel Computing. LCPC 2008. Lecture Notes in Computer Science, vol 5335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89740-8_9
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DOI: https://doi.org/10.1007/978-3-540-89740-8_9
Publisher Name: Springer, Berlin, Heidelberg
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