Abstract
In this paper we present results we obtained using a compiler to predict performance of scientific codes. The compiler, Polaris [3], is both the primary tool for estimating the performance of a range of codes, and the beneficiary of the results obtained from predicting the program behavior at compile time. We show that a simple compile-time model, augmented with profiling data obtained using very light instrumentation, can be accurate within 20% (on average) of the measured performance for codes using both dense and sparse computational methods.
This work is supported in part by Army contract DABT63-95-C-0097; Army contract N66001-97-C-8532; NSF contract MIP-9619351; and a Partnership Award from IBM. This work is not necessarily representative of the positions or policies of the Army or Government.
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Cascaval, C., DeRose, L., Padua, D.A., Reed, D.A. (2000). Compile-Time Based Performance Prediction. In: Carter, L., Ferrante, J. (eds) Languages and Compilers for Parallel Computing. LCPC 1999. Lecture Notes in Computer Science, vol 1863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44905-1_23
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