We describe an approach to data analytics on large systems using a suite of robust parallel algorithms running on both clouds and HPC systems. We apply this to cases where the data is defined in a vector space and when only pairwise distances between points are defined. We introduce improvements to known algorithms for functionality, features and performance but review state of the art as this ...

in today’s competitive transportation systems, passengers search to find traveling agencies that are able to serve them efficiently considering both traveling time and transportation costs. in this paper, we present a new model for the traveling salesman problem with multiple transporters (tspmt). in the proposed model, which is more applicable than the traditional versions, each city has diffe...

A delivery problem which reduces to the NP-complete set-partitioning problem is investigated. The sequential and parallel simulated annealing algorithms to solve the delivery problem are discussed. The objective is to improve the quality of solutions to the problem by applying parallelism.

Analog synthesis tools have failed to migrate into mainstream use primarily because of difficulties in reconciling the simplified models required for synthesis with the industrial-strength simulation environments required for validation. MAELSTROM is a new approach that synthesizes a circuit using the same simulation environment created to validate the circuit. We introduce a novel genetic/ ann...

In the design of multicomputer systems, the scheduling and mapping of a parallel algorithm onto a host architecture has a critical impact on overall system performance. In this paper we develop a graph-based solution to both aspects of the mapping problem using the simulated annealing optimization heuristic. A two phase mapping strategy is formulated: I) process annealing assigns parallel proce...