CORE :: Comprehensive Optimization via Regression Estimates

CORE is a collection of example R scripts that construct microarchitectural performance and power regression models. These models are based on restricted cubic splines. The derivation process includes correlation, association, clustering, and significance analyses. The current scripts illustrate model construction for out-of-order, superscalar architectures using data from the IBM Turandot/PowerTimer simulation infrastructure, which simulates a POWER4/5-like architecture.

The code implements statistical techniques for exploratory data analysis (correlation, association, clustering, significance testing) using the open source R statistical computing package. For downloads and installation instructions of the R package, refer to its website.

[Download] Data for formulating regression models
[Download] Code for data analysis and regression modeling
[Website] The R Project for Statistical Computing

This data and code are to accompany the paper "Accurate and efficient regression modeling for microarchitectural performance and power prediction" in the proceedings of the International Conference on Architectural Support for Programming Languages and Operating Systems [ASPLOS'06] . For a detailed explanation of the code and analysis, please refer to the following tutorial [IEEE'07]. Further information may be found in the technical report leading up to the ASPLOS 2006 paper [TR'06].

OSKI :: Optimized Sparse Kernel Interface

The Optimized Sparse Kernel Interface (OSKI) Library is a collection of low-level C primitives that provide automatically tuned computational kernels on sparse matrices, for use in solver libraries and applications. OSKI has a BLAS-style interface, providing basic kernels like sparse matrix-vector multiply and sparse triangular solve, among others.

[Website] BeBOP Optimized Sparse Kernel Interface