Simulations among concurrent-write PRAMs

This paper is concerned with the relative power of the two most popular concurrent-write models of parallel computation, the PRIORITY PRAM [G], and the COMMON PRAM [K]. Improving the trivial and seemingly optimalO(logn) simulation, we show that one step of a PRIORITY machine can be simulated byO(logn/(log logn)) steps of a COMMON machine with the same number of processors (and more memory). We further prove that this is optimal, if processor communication is restricted in a natural way.     

Efficient Deterministic and Probabilistic Simulations of PRAMs on Linear Arrays with Reconfigurable Pipelined Bus Systems

In this paper, we present deterministic and probabilistic methods for simulating PRAM computations on linear arrays with reconfigurable pipelined bus systems (LARPBS). The following results are established in this paper. (1) Each step of a p-processor PRAM with m=O(p) shared memory cells can be simulated by a p-processors LARPBS in O(log p) time, where the constant in the big-O notation is small. (2) Each step of a p-processor PRAM with m=(p) shared memory cells can be simulated by a p-processors LARPBS in O(log m) time. (3) Each step of a p-processor PRAM can be simulated by a p-processor LARPBS in O(log p) time with probability larger than 1–1/p^c for all c>0. (4) As an interesting byproduct, we show that a p-processor LARPBS can sort p items in O(log p) time, with a small constant hidden in the big-O notation. Our results indicate that an LARPBS can simulate a PRAM very efficiently.     

Lower bounds on precedence-constrained scheduling for parallel processors

We consider two general precedence-constrained scheduling problems that have wide applicability in the areas of parallel processing, high performance compiling, and digital system synthesis. These problems are intractable so it is important to be able to compute tight bounds on their solutions. A tight lower bound on makespan scheduling can be obtained by replacing precedence constraints with release and due dates, giving a problem that can be efficiently solved. We demonstrate that recursively applying this approach yields a bound that is provably tighter than other known bounds, and experimentally shown to achieve the optimal value at least 90.3% of the time over a synthetic benchmark.We compute the best known lower bound on weighted completion time scheduling by applying the recent discovery of a new algorithm for solving a related scheduling problem. Experiments show that this bound significantly outperforms the linear programming-based bound. We have therefore demonstrated that combinatorial algorithms can be a valuable alternative to linear programming for computing tight bounds on large scheduling problems.     

Large parallel machines can be extremely slow for small problems

We consider concurrent-write PRAMs with a large number of processors of unlimited computational power and an infinite shared memory. Our adversary chooses a small number of our processors and gives them a 0–1 input sequence (each chosen processor gets a bit, and each bit is given to one processor). The chosen processors are required to compute thePARITY of their input, while the others do not take part in the computation. Ifat most q processors are chosen andq 1/2 log logn, then we show that computing PARITY needsq steps in the worst case. On the other hand, there exists an algorithm which computes PARITY inq steps (for anyq <n) in this model, thus our result is sharp. Surprisingly, if our adversary choosesexactly q of our processors, then they can compute PARITY in [q/2] + 2 steps, and in this case we show that it needs at least [q2] steps. Our result implies that large parallel machines which are efficient when only a small number of their processors are active cannot be constructed. On the other hand, a result of Ajtai and Ben-Or [1] shows that if we haven input bits which contain at most polylogn 1's and polynomially many processors which are all allowed to work, then thePARITY can be solved inconstant time.     

FORK: A high-level language for PRAMs

We present a new programming language designed to allow the convenient expression of algorithms for a parallel random access machine (PRAM). The language attempts to satisfy two potentially conflicting goals: On the one hand, it should be simple and clear enough to serve as a vehicle for human-to-human communication of algorithmic ideas. On the other hand, it should be automatically translatable to efficient machine (i.e. PRAM) code, and it should allow precise statements to be made about the amount of resources (primarily time) consumed by a given program. In the sequential setting, both objectives are reasonably well met by the Algol-like languages, e.g. with the RAM as the underlying machine model, but we are not aware of any language that allows a satisfactory expression of typical PRAM algorithms. Our contribution should be seen as a modest attempt to fill this gap.     

Fast integer merging on the EREW PRAM

We investigate the complexity of merging sequences of small integers on the EREW PRAM. Our most surprising result is that two sorted sequences ofn bits each can be merged inO(log logn) time. More generally, we describe an algorithm to merge two sorted sequences ofn integers drawn from the set {0, ...,m?1} inO(log logn+log min{n, m}) time with an optimal time-processor product. No sublogarithmic-time merging algorithm for this model of computation was previously known. On the other hand, we show a lower bound of Ω(log min{n, m}) on the time needed to merge two sorted sequences of lengthn each with elements drawn from the set {0, ...,m?1}, implying that our merging algorithm is as fast as possible form=(logn)^Ω(1). If we impose an additional stability condition requiring the elements of each input sequence to appear in the same order in the output sequence, the time complexity of the problem becomes Θ(logn), even form=2. Stable merging is thus harder than nonstable merging.     

Finding all periods and initial palindromes of a string in parallel

An optimalO(log logn)-time CRCW-PRAM algorithm for computing all period lengths of a string is presented. Previous parallel algorithms compute the period only if it is shorter than half of the length of the string. The algorithm can be used to find all initial palindromes of a string in the same time and processor bounds. Both algorithms are the fastest possible over a general alphabet. We derive a lower bound for finding initial palindromes by modifying a known lower bound for finding the period length of a string [9]. Whenp processors are available the bounds become (n/p+log_1+p/n2p).This work was partially supported by NSF Grant CCR-90-14605. D. Breslauer was partially supported by an IBM Graduate Fellowship while studying at Columbia University and by a European Research Consortium for Informatics and Mathematics postdoctoral fellowship.     

Efficient parallel algorithms can be made robust

Summary The efficient parallel algorithms proposed for many fundamental problems, such as list ranking, integer sorting and computing preorder numberings on trees, are very sensitive to processor failures. The requirement of efficiency (commonly formalized usingParallel-timexProcessors as a cost measure) has led to the design of highly tuned PRAM algorithms which, given the additional constraint of simple processor failures, unfortunately become inefficient or even incorrect. We propose a new notion ofrobustness, that combines efficiency with fault tolerance. For the common case of fail-stop errors, we develop a general and easy to implement technique to make robust many efficient parallel algorithms, e.g., algorithms for all the problems listed above. More specifically,for any dynamic pattern of fail-stop errors on a CRCW PRAMwith at least one surviving processor, our method increases the original algorithm cost by at most a log² multiplicative factor. Our technique is based on a robust solution of the problem ofWrite-All, i.e., usingP processors, write 1's in all locations of anN-sized array. In addition we show that at least a log/log log multiplicative overhead will be incurred for certain patterns of failures by any algorithm that implements robust solutions toWrite-All withP=N. However, by exploiting parallel slackness, we obtain an optimal cost algorithm when Paris C. Kanellakis is a professor of computer science at Brown University. His primary research interests are in the application of logic to computer science, such as high-level query languages for database systems, parallel evaluation of logic programs, and type inference for programming languages. He has published many articles on these subjects and is the author of the chapter Elements of Relational Database Theory in theHandbook of Theoretical Computer Science (Elsevier, 1990). He has also contributed to the theory of distributed computing and to combinatorial optimization. Alex Allister Shvartsman is an engineer at Digital Equipment Corporation. His professional interests include design and development of efficient distributed systems, distributed resource management, and theoretical foundations of fault-tolerant parallel computation. At Digital he architected and managed the development of distributed control systems that automated several of Digital's manufacturing processes. He is currently on an academic leave at Brown University.An extended abstract of a part of this work appears as: Kanellakis and Shvartsman (1989) in the Proceedings of the 8th ACM Symposium on Principles of Distributed Computing, Edmonton 1989This author was supported by NSF grant IRI-8617344, an Alfred P. Sloan fellowship and ONR grant N00014-83-K-0146 ARPA Order No. 4786This author was supported by DEC GEEP Doctoral program and ONR grant N00014-91-J-1613     

The Temporal Precedence Problem

In this paper we analyze the complexity of the Temporal Precedence Problem on pointer machines. The problem is to support efficiently two operations: insert and precedes. The operation insert (a) introduces a new element a , while precedes (a,b) returns true iff element a was temporally inserted before element b . We provide a solution to the problem with worst-case time complexity O( lg lg n) per operation, where n is the number of elements inserted. We also demonstrate that the problem has a lower bound of Ω( lg lg n) on pointer machines. Thus the proposed scheme is optimal on pointer machines. Received February 5, 1998; revised October 21, 1998.     

On the complexity of global computation in the presence of link failures: the general case

Summary This paper presents (m logn) and (mn) messages lower bounds on the problem of computing a gobal sensitive function in biderectional networks with link failures (i.e., dynamically changing topology), wheren andm are the total number of nodes and links in the network. The (m logn) lower bound is under the assumption thatn is a-priori known to the nodes, while the second bound is for the case in which such knowledge is not available. A global sensitive function ofn variables is a function that may not be computed without the knowledge of the values of all then variables (e.g. maximum, sum, etc). Thus, computing such a function at one node of a distributed network requires this node to communicate with every other node in the network. Though lower bounds higher than (m) messages are known for this problem in the context of link failures, none holds for dense bidirectional networks. Moreover, we are not aware of any other nontrivial lower bound higher than (m) for dense bidirectional networks. Yehuda Afek received a B.Sc. in Electrical Engineering from the Technion and an M.Sc. and Ph.D. in Computer Science from the University of California, Los-Angeles. In 1985 he joined the Distributed Systems Research Department in AT&T Bell Laboratories as a Member of Technical Staff. In 1988 he joined the Computer Science Department in Tel-Aviv University, where he now holds a permanent position. From 1989 to 1994 he was also a consultant for AT&T Bell Laboratories. His interests include communication protocols, distributed computing and asynchronous shared memory systems. Danny Hendler was born in Kiryat-Haim near Haifa, Israel, on April 17th 1961. He received his B.Sc. and M.Sc. in Computer Science from Tel-Aviv University, Israel, in 1986 and 1993, respectively. In the past 8 years he has worked as a free lance software-consultant, specializing mainly in communication, telephony and voice-mail applications.     

New bin packing fast lower bounds

In this paper, we address the issue of computing fast lower bounds for the Bin Packing problem, i.e., bounds that have a computational complexity dominated by the complexity of ordering the items by non-increasing values of their volume. We introduce new classes of fast lower bounds with improved asymptotic worst-case performance compared to well-known results for similar computational effort. Experimental results on a large set of problem instances indicate that the proposed bounds reduce both the deviation from the optimum and the computational effort.     

An efficient parallel strategy for the perfect domination problem on distance-hereditary graphs

A graph is distance-hereditary if the distance stays the same between any of two vertices in every connected induced subgraph containing both. Two well-known classes of graphs, trees and cographs, both belong to distance-hereditary graphs. In this paper, we first show that the perfect domination problem can be solved in sequential linear-time on distance-hereditary graphs. By sketching some regular property of the problem, we also show that it can be easily parallelized on distance-hereditary graphs.     

信息分组随机争用信道时隙数学模型分析

对随机接入系统树型冲突分解过程中信息分组争用信道建立了数学模型,通过采用排列-组合计数方法中的划分思想对其进行分析,得到了各种数学模型的数学解析式,对几个重要定理,给出了严格的证明,这些定理对随机系统中树型冲突分解算法的研究具有重要的意义。     

The complexity of updating snapshot objects

This paper proves Ω(m) lower bounds on the step complexity of UPDATE operations for space-optimal wait-free implementations of an m-component snapshot object from historyless objects. These lower bounds follow from lower bounds for a new, more general class of implementations from base objects of any type. This work extends a similar lower bound by Israeli and Shirazi for implementations of m-component single-writer snapshot objects from single-writer registers.     

A parallel algorithm for approximate regularity

Spatial regularity amidst a seemingly chaotic image is often meaningful. Many papers in computational geometry are concerned with detecting some type of regularity via exact solutions to problems in geometric pattern recognition. However, real-world applications often have data that is approximate, and may rely on calculations that are approximate. Thus, it is useful to develop solutions that have an error tolerance.

A solution has recently been presented by Robins et al. [Inform. Process. Lett. 69 (1999) 189–195] to the problem of finding all maximal subsets of an input set in the Euclidean plane that are approximately equally-spaced and approximately collinear. This is a problem that arises in computer vision, military applications, and other areas. The algorithm of Robins et al. is different in several important respects from the optimal algorithm given by Kahng and Robins [Patter Recognition Lett. 12 (1991) 757–764] for the exact version of the problem. The algorithm of Robins et al. seems inherently sequential and runs in O(n^5/2) time, where n is the size of the input set. In this paper, we give parallel solutions to this problem.     

A new scheme for the deterministic simulation of PRAMs in VLSI

A deterministic scheme for the simulation of (n, m)-PRAM computation is devised. Each PRAM step is simulated on a bounded degree network consisting of a mesh-of-trees (MT) of siden. The memory is subdivided inn modules, each local to a PRAM processor. The roots of the MT contain these processors and the memory modules, while the otherO(n ²) nodes have the mere capabilities of packet switchers and one-bit comparators. The simulation algorithm makes a crucial use of pipelining on the MT, and attains a time complexity ofO(log² n/log logn). The best previous time bound wasO(log² n) on a different interconnection network withn processors. While the previous simulation schemes use an intermediate MPC model, which is in turn simulated on a bounded degree network, our method performs the simulation directly with a simple algorithm.This work has been supported in part by Ministero della Pubblica Istruzione of Italy under a research grant.     

A new lower bound for curriculum-based course timetabling

In this paper, we propose a new method to compute lower bounds for curriculum-based course timetabling (CTT), which calls for the best weekly assignment of university course lectures to rooms and time slots. The lower bound is obtained by splitting the objective function into two parts, considering one separate problem for each part of the objective function, and summing up the corresponding optimal values (or, in some cases, lower bounds on these values), found by formulating the two parts as Integer Linear Programs (ILPs). The solution of one ILP is obtained by using a column generation procedure. Experimental results show that the proposed lower bound is often better than the ones found by the previous methods in the literature, and also much better than those found by other new ILP formulations illustrated in this paper. The proposed approach is able to obtain improved lower bounds on real-world benchmark instances from the literature, used in the international timetabling competitions ITC2002 and ITC2007, proving for the first time that some of the best-known heuristic solutions are indeed optimal (or close to the optimal ones).     

New lower bound for the Capacitated Arc Routing Problem

We present a new lower bound, the Multiple Cuts Node Duplication Lower Bound, for the undirected Capacitated Arc Routing Problem. We prove that this new bound dominates the existing bounds for the problem. Computational results are also provided.     

A tight lower bound for job scheduling with cancellation

The Job Scheduling with Cancellation problem is a variation of classical scheduling problems in which jobs can be cancelled while waiting for execution. In this paper we prove a tight lower bound of 5 for the competitive ratio of any deterministic online algorithm for this problem, for the case where all jobs have the same processing time.     

A branch-and-price algorithm for the general case of scheduling parallel machines with a single server

We consider the strongly NP-hard problem of scheduling two-operation non-preemptable jobs on two identical parallel machines. A single server, that can handle at most one job at a time, is available to carry out the first (or setup) operation. The second operation, to be carried out on the same machine but without the server, must be executed immediately after the setup. The objective is to minimize the makespan. We apply a column generation method to a population of partial schedules, in turn generated by some well known heuristics, to achieve effective and efficient solutions. We compare the performance of this method with those proposed earlier and also suggest future work.