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20132026
most citedQSGD: Communication-Efficient SGD via Gradient Quantization and Encoding

908 citations · 2.4k across the 149 of their papers we have counts for

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13 papers · 1 filter

cs.DS2026

GPTQ-2D: Cubic-Time Two-Sided Adaptive Rounding

Jiale Chen, Torsten Hoefler, Dan Alistarh

Adaptive rounding methods such as GPTQ, or equivalently Babai's nearest plane algorithm, round a real matrix to integers under a quadratic metric. They process the entries in a fix…

cs.DS2023

Efficient Self-Adjusting Search Trees via Lazy Updates

Alexander Slastin, Dan Alistarh, Vitaly Aksenov

Self-adjusting data structures are a classic approach to adapting the complexity of operations to the data access distribution. While several self-adjusting variants are known for…

cs.DS2023★ 3 cited

Provably-Efficient and Internally-Deterministic Parallel Union-Find

Alexander Fedorov, Diba Hashemi, Giorgi Nadiradze +1

Determining the degree of inherent parallelism in classical sequential algorithms and leveraging it for fast parallel execution is a key topic in parallel computing, and detailed a…

cs.DS2022

Fast and Scalable Channels in Kotlin Coroutines

Nikita Koval, Dan Alistarh, Roman Elizarov

Asynchronous programming has gained significant popularity over the last decade: support for this programming pattern is available in many popular languages via libraries and nativ…

cs.DS2021

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…

cs.DS2021

A Scalable Concurrent Algorithm for Dynamic Connectivity

Alexander Fedorov, Nikita Koval, Dan Alistarh

Dynamic Connectivity is a fundamental algorithmic graph problem, motivated by a wide range of applications to social and communication networks and used as a building block in vari…

cs.DS2020★ 4 cited

Efficiency Guarantees for Parallel Incremental Algorithms under Relaxed Schedulers

Dan Alistarh, Nikita Koval, Giorgi Nadiradze

Several classic problems in graph processing and computational geometry are solved via incremental algorithms, which split computation into a series of small tasks acting on shared…

cs.DS2020

Dynamic Averaging Load Balancing on Cycles

Dan Alistarh, Giorgi Nadiradze, Amirmojtaba Sabour

We consider the following dynamic load-balancing process: given an underlying graph with nodes, in each step , one unit of load is created, and placed at a randoml…

cs.DS2020★ 1 cited

Analysis and Evaluation of Non-Blocking Interpolation Search Trees

Aleksandar Prokopec, Trevor Brown, Dan Alistarh

We start by summarizing the recently proposed implementation of the first non-blocking concurrent interpolation search tree (C-IST) data structure. We then analyze the individual o…

cs.DS2019

In Search of the Fastest Concurrent Union-Find Algorithm

Dan Alistarh, Alexander Fedorov, Nikita Koval

Union-Find (or Disjoint-Set Union) is one of the fundamental problems in computer science; it has been well-studied from both theoretical and practical perspectives in the sequenti…

cs.DS2018★ 13 cited

Relaxed Schedulers Can Efficiently Parallelize Iterative Algorithms

Dan Alistarh, Trevor Brown, Justin Kopinsky +1

There has been significant progress in understanding the parallelism inherent to iterative sequential algorithms: for many classic algorithms, the depth of the dependence structure…

cs.DS2017★ 2 cited

The Power of Choice in Priority Scheduling

Dan Alistarh, Justin Kopinsky, Jerry Li +1

Consider the following random process: we are given queues, into which elements of increasing labels are inserted uniformly at random. To remove an element, we pick two queues…

cs.DS2017★ 4 cited

Robust Detection in Leak-Prone Population Protocols

Dan Alistarh, Bartłomiej Dudek, Adrian Kosowski +2

In contrast to electronic computation, chemical computation is noisy and susceptible to a variety of sources of error, which has prevented the construction of robust complex system…