908 citations · 2.4k across the 149 of their papers we have counts for
16 papers · 1 filter
Collecting Coupons is Faster with Friends
Dan Alistarh, Peter Davies
In this note, we introduce a distributed twist on the classic coupon collector problem: a set of collectors wish to each obtain a set of coupons; for this, they can each sa…
How Well Do Sparse Imagenet Models Transfer?
Eugenia Iofinova, Alexandra Peste, Mark Kurtz +1
Transfer learning is a classic paradigm by which models pretrained on large "upstream" datasets are adapted to yield good results on "downstream" specialized datasets. Generally, m…
CQS: A Formally-Verified Framework for Fair and Abortable Synchronization
Nikita Koval, Dmitry Khalanskiy, Dan Alistarh
Writing concurrent code that is both correct and efficient is notoriously difficult. Thus, programmers often prefer to use synchronization abstractions, which render code simpler a…
CGX: Adaptive System Support for Communication-Efficient Deep Learning
Ilia Markov, Hamidreza Ramezanikebrya, Dan Alistarh
The ability to scale out training workloads has been one of the key performance enablers of deep learning. The main scaling approach is data-parallel GPU-based training, which has…
Distributed Principal Component Analysis with Limited Communication
Foivos Alimisis, Peter Davies, Bart Vandereycken +1
We study efficient distributed algorithms for the fundamental problem of principal component analysis and leading eigenvector computation on the sphere, when the data are randomly…
Multi-Queues Can Be State-of-the-Art Priority Schedulers
Anastasiia Postnikova, Nikita Koval, Giorgi Nadiradze +1
Designing and implementing efficient parallel priority schedulers is an active research area. An intriguing proposed design is the Multi-Queue: given threads and disti…