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In each step of the $p$-processor cup game on $n$ cups, a filler distributes up to $p$ units of water among the cups, subject only to the constraint that no cup receives more than $1$ unit of water; an emptier then removes up to $1$ unit of…

Data Structures and Algorithms · Computer Science 2019-10-31 William Kuszmaul

In the cup game, an adversary distributes 1 unit of water among $n$ cups every time step. The player then selects a single cup from which to remove 1 unit of water. In the bamboo trimming problem, the adversary must choose fixed rates for…

Data Structures and Algorithms · Computer Science 2026-02-24 Kalina Jasińska , John Kuszmaul , Gyudong Lee

The problem of scheduling tasks on $p$ processors so that no task ever gets too far behind is often described as a game with cups and water. In the $p$-processor cup game on $n$ cups, there are two players, a filler and an emptier, that…

Data Structures and Algorithms · Computer Science 2021-02-11 William Kuszmaul , Alek Westover

The \emph{$ p$-processor cup game} is a classic and widely studied scheduling problem that captures the setting in which a $p$-processor machine must assign tasks to processors over time in order to ensure that no individual task ever falls…

Data Structures and Algorithms · Computer Science 2022-07-26 William Kuszmaul , Shyam Narayanan

The cup game on $n$ cups is a multi-step game with two players, a filler and an emptier. At each step, the filler distributes $1$ unit of water among the cups, and then the emptier selects a single cup to remove (up to) $1$ unit of water…

Data Structures and Algorithms · Computer Science 2021-04-13 William Kuszmaul

We study the minimum backlog problem (MBP). This online problem arises, e.g., in the context of sensor networks. We focus on two main variants of MBP. The discrete MBP is a 2-person game played on a graph $G=(V,E)$. The player is initially…

We consider the problem of energy-efficient scheduling across multiple processors with a power-down mechanism. In this setting a set of $n$ jobs with individual release times, deadlines, and processing volumes must be scheduled across $m$…

Data Structures and Algorithms · Computer Science 2023-07-04 Gunther Bidlingmaier

The submodular maximization problem is widely applicable in many engineering problems where objectives exhibit diminishing returns. While this problem is known to be NP-hard for certain subclasses of objective functions, there is a greedy…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-07-01 Haoyuan Sun , David Grimsman , Jason R Marden

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi

We consider an infinite balls-into-bins process with deletions where in each discrete step $t$ a coin is tossed as to whether, with probability $\beta(t) \in (0,1)$, a new ball is allocated using the Greedy[2] strategy (which places the…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-17 Petra Berenbrink , Tom Friedetzky , Peter Kling , Lars Nagel

This paper proposes a greedy algorithm named as Big step greedy set cover algorithm to compute approximate minimum set cover. The Big step greedy algorithm, in each step selects p sets such that the union of selected p sets contains…

Data Structures and Algorithms · Computer Science 2015-06-16 Drona Pratap Chandu

Collective communications are ubiquitous in parallel applications. We present two new algorithms for performing a reduction. The operation associated with our reduction needs to be associative and commutative. The two algorithms are…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-10-18 Bradley R. Lowery , Julien Langou

This paper studies the online scheduling problem of minimizing total flow time for $n$ jobs on $m$ identical machines. A classical $\Omega(n)$ lower bound shows that no deterministic single-machine algorithm can beat the trivial greedy,…

Data Structures and Algorithms · Computer Science 2026-04-02 Yutong Geng , Enze Sun , Zonghan Yang , Yuhao Zhang

An effective technique for solving optimization problems over massive data sets is to partition the data into smaller pieces, solve the problem on each piece and compute a representative solution from it, and finally obtain a solution…

Data Structures and Algorithms · Computer Science 2015-06-23 Vahab Mirrokni , Morteza Zadimoghaddam

Many problems in signal processing and machine learning can be formalized as weak submodular optimization tasks. For such problems, a simple greedy algorithm (\textsc{Greedy}) is guaranteed to find a solution achieving the objective with a…

Discrete Mathematics · Computer Science 2021-11-24 Abolfazl Hashemi , Haris Vikalo , Gustavo de Veciana

We consider a parallel system of $m$ identical machines prone to unpredictable crashes and restarts, trying to cope with the continuous arrival of tasks to be executed. Tasks have different computational requirements (i.e., processing time…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-21 Elli Zavou , Antonio Fernández Anta

In this paper, we consider the online problem of scheduling independent jobs \emph{non-preemptively} so as to minimize the weighted flow-time on a set of unrelated machines. There has been a considerable amount of work on this problem in…

Data Structures and Algorithms · Computer Science 2018-04-24 Giorgio Lucarelli , Benjamin Moseley , Nguyen Kim Thang , Abhinav Srivastav , Denis Trystram

We consider 2-player games played on a finite state space for infinite rounds. The games are concurrent: in each round, the two players choose their moves simultaneously; the current state and the moves determine the successor. We consider…

Computer Science and Game Theory · Computer Science 2013-06-21 Krishnendu Chatterjee

The Greedy algorithm is the simplest heuristic in sequential decision problem that carelessly takes the locally optimal choice at each round, disregarding any advantages of exploring and/or information gathering. Theoretically, it is known…

Machine Learning · Computer Science 2021-01-05 Matthieu Jedor , Jonathan Louëdec , Vianney Perchet

We consider the online minimum cost matching problem on the line, in which there are $n$ servers and, at each of $n$ time steps, a request arrives and must be irrevocably matched to a server that has not yet been matched to, with the goal…

Data Structures and Algorithms · Computer Science 2025-03-28 Eric Balkanski , Yuri Faenza , Noemie Perivier
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