Identifying Merge-Beneficial Software Kernels for Hardware Implementation

• Type: Article in International Conference Proceedings Book
• Date: 2011

Authors

Sanches, AK (Author) Other; João M. P. Cardoso (Author) FEUP; Delbem, ACB (Author) Other

Conference proceedings International

Title: 2011 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2011, Cancun, Mexico, November 30 - December 2, 2011

Pages: 74-79

2011 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2011

Cancun, Quintana Roo, 30 November 2011 through 2 December 2011

Indexing

Scopus - 16 Citations

Other information

Authenticus ID: P-008-2EY

DOI: 10.1109/ReConFig.2011.51

Abstract (EN): Data-mining over software can reveal similar patterns on software code. This can give important insights for the design of hardware cores, especially considering the benefits of the merge of software kernels and their implementation as a single hardware core. However, software codes have characteristics that make inadequate the direct use of typical data mining tools, mainly related to their large number of samples and the imprecise definition of code features for mining. Those characteristics affect negatively the performance of the most known data mining methods. To solve this problem, we propose in this paper the use of three techniques: the Normalized Compression Distance, the Neighbor Joining, and the Fast Newman algorithm. We combine these three techniques and propose a new approach for data mining of code repositories (DAMICORE). DAMICORE works with different types of code representations. Experiments reveal DAMICORE can indicate important software similarities at source code level. Specifically, merging soft-ware kernels identified by DAMICORE results in FPGA cores with size smaller than the overall hardware size needed when implementing a core for each kernel. © 2011 IEEE.

Language: English

Type (Professor's evaluation): Scientific