Jon Lee, Maxim Sviridenko, et al.
SIAM Journal on Computing
We provide a first demonstration of the idea that matrix-based algorithms for nonlinear combinatorial optimization problems can be efficiently implemented. Such algorithms were mainly conceived by theoretical computer scientists for proving efficiency. We are able to demonstrate the practicality of our approach by developing an implementation on a massively parallel architecture, and exploiting scalable and efficient parallel implementations of algorithms for ultra high-precision linear algebra. Additionally, we have delineated and implemented the necessary algorithmic and coding changes required in order to address problems several orders of magnitude larger, dealing with the limits of scalability from memory footprint, computational efficiency, reliability, and interconnect perspectives. © Springer and Mathematical Programming Society 2010.
Jon Lee, Maxim Sviridenko, et al.
SIAM Journal on Computing
Jon Lee
J Combin Optim
Jon Lee, Janny Leung, et al.
J Combin Optim
Vijay S. Iyengar, Jon Lee, et al.
ACM Conference on Electronic Commerce 2001