The Report of the SDPA Project in August, 2008.

The SDPA Project started in 1995 have provided several software packages for solving large-scale Semide nite Programs(SDPs). The SDPA 6.2.1 attained high performance for large-scale dense SDPs, however, it required much computation time compared with other software packages when the Schur complement matrix is sparse. The SDPA 7.1.1 is completely revised from its source code, and there are great performance improvements on its computation time and memory usage.
The objective of this paper is to present brief explanations of the SDPA 7.1.1 and its high performance for large-scale dense and sparse SDPs through numerical experiments compared with some other major software packages for general SDPs. We also review the major achievements of the SDPA Project on solving large-scale SDPs.
The PDF file of the presentation in SJOM 2008 is available from here.

The Shortest Path Online and GoogleMaps

The Shortest Path Online is currently working in cooperation with the GoogleMaps. Users can input starting and ending points on the GoogleMaps. Note that inside points of the USA are only available, because we have only data files of the USA, which contain nodes, their coordinates and so on.
We have implemented the Dijkstra algorithm with heap and bucket data structure. The memory hierarchy is carefully considered to specify the bottleneck of the algorithm and improve the performance. This implementation can solve large-scale shortest path problem quickly.
The online solver can also display shortest paths on the GoogleMaps. The figure attached in this article shows two shortest paths. The red and blue paths denote the shortest paths to minimize the total distance and time between the starting and ending points, respectively.