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Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Bibliography
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Bibliography


Section: New Results

Asaga: Asynchronous Parallel Saga

In [29], we describe Asaga, an asynchronous parallel version of the incremental gradient algorithm Saga that enjoys fast linear convergence rates. We highlight a subtle but important technical issue present in a large fraction of the recent convergence rate proofs for asynchronous parallel optimization algorithms, and propose a simplification of the recently proposed “perturbed iterate” framework that resolves it. We thereby prove that Asaga can obtain a theoretical linear speedup on multi-core systems even without sparsity assumptions. We present results of an implementation on a 40-core architecture illustrating the practical speedup as well as the hardware overhead.