USA flag logo/image

An Official Website of the United States Government

Accelerating ATM Optimization Algorithms Using High Performance Computing…

Award Information

Agency:
National Aeronautics and Space Administration
Branch:
N/A
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
105968
Solicitation Year:
2010
Solicitation Topic Code:
A3.01
Solicitation Number:
Small Business Information
Optimal Synthesis, Inc.
95 First Street, Suite 240 Los Altos, CA 94022-2777
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 2012
Title: Accelerating ATM Optimization Algorithms Using High Performance Computing Hardware
Agency: NASA
Contract: NNX12CA05C
Award Amount: $750,000.00
 

Abstract:

NASA is developing algorithms and methodologies for efficient air-traffic management. Several researchers have adopted an optimization framework for solving problems such as flight scheduling, route assignment, flight rerouting, nationwide traffic flow management (TFM) and dynamic airspace configuration. Computational complexity of these problems have led investigators to conclude that in many instances, real time solutions are computationally infeasible, forcing the use of relaxed versions of the problem to manage computational complexity. The primary objective of the proposed research is to accelerate optimization algorithms that play central roles in NASA's ATM research, by parallel implementation on emerging high performance computing (HPC) hardware.The Phase I R & D effort implemented a Simplex-based Dantzig-Wolfe (DW) decomposition solver that exploits both coarse-grain and fine-grain parallelism in the sub-problem and master iterations of the DW decomposition. The implementation also exploits the sparsity in the problems, to manage both memory requirements and run-times for large-scale optimization problems. This parallel implementation was used to solve a Traffic Flow Management (TFM) problem with 17,000 aircraft (linear program with 7 million constraints), in 15 seconds. The implementation is 30¿ faster than the exact same code running on the CPU. It is also 16¿ faster than the NASA's current solution that implements parallel DW decomposition using the GNU Linear Programming Kit (GLPK) on an 8-core computer with hyper-threading.Based on the promising Phase I results, the Phase II R & D effort will explore Mixed Integer Linear Programming (MILP) methods to solve optimization problems arising in the terminal area and on the airport surface, in addition to DW decomposition for the nationwide TFM problem. Phase II work will develop operational prototypes of the algorithm implementations on HPC hardware, and deliver them to NASA for further evaluation.

Principal Investigator:

Monish D. Tandale
Principal Investigator
6505598585
monish@optisyn.com

Business Contact:

P. k. Menon
Business Official
6505598585
menon@optisyn.com
Small Business Information at Submission:

Optimal Synthesis, Inc.
95 First Street, Suite 240 Los Altos, CA 94022-2777

EIN/Tax ID: 770484755
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No