9141341
Dependent rounding and its applications to approximation algorithms
We develop a new randomized rounding approach for fractional vectors defined on the edge-sets of bipartite graphs. We show various ways of combining this technique with other ideas, leading to improved (approximation) algorithms for various problems. These include:---low congestion multi-path routing;---richer random-graph models for graphs with a given degree-sequence;---improved approximation algorithms for: (i) throughput-maximization in broadcast scheduling, (ii) delay-minimization in broadcast scheduling, as well as (iii) capacitated vertex cover; and---fair scheduling of jobs on unrelated parallel machines.
5564142
Provable algorithms for parallel generalized sweep scheduling
Abstract We present provably efficient parallel algorithms for sweep scheduling, which is a commonly used technique in radiation transport problems, and involves inverting an operator by iteratively sweeping across a mesh from multiple directions. Each sweep involves solving the operator locally at each cell. However, each direction induces a partial order in which this computation can proceed. On a distributed computing system, the goal is to schedule the computation, so that the length of the schedule is minimized. Due to efficiency and coupling considerations, we have an additional constraint, namely, a mesh cell must be processed on the same processor along each direction. Problems similar in nature to sweep scheduling arise in several other applications, and here we formulate a combinatorial generalization of this problem that captures the sweep scheduling constraints,and call it the generalized sweep scheduling problem. Several heuristics have been proposed for this problem; see [S. Pautz, An algorithm for parallel S n sweeps on unstructured meshes, Nucl. Sci. Eng. 140 (2002) 111–136; S. Plimpton, B. Hendrickson, S. Burns, W. McLendon, Parallel algorithms for radiation transport on unstructured grids, Super Comput. (2001)] and the references therein; but none of these have provable worst case performance guarantees. Here we present a simple, almost linear time randomized algorithm for the generalized sweep scheduling problem that (provably) gives a schedule of length at most O ( log 2 n ) times the optimal schedule for instances with n cells, when the communication cost is not considered, and a slight variant, which coupled with a much more careful analysis, gives a schedule of (expected) length O ( log m log log log m ) times the optimal schedule for m processors. These are the first such provable guarantees for this problem. The algorithm can be extended with an additional multiplicative factor in the case when we have inter-processor communication latency, in the models of Rayward-Smith [UET scheduling with inter-processor communication delays, Discrete Appl. Math. 18 (1) (1987) 55–71] and Hwang et al. [Scheduling precedence graphs in systems with inter-processor communication times, SIAM J. Comput. 18(2) (1989) 244–257]. Our algorithms are extremely simple, and use no geometric information about the mesh; therefore, these techniques are likely to be applicable in more general settings. We also design a priority based list schedule using these ideas, with the same theoretical guarantee, but much better performance in practice; combining this algorithm with a simple block decomposition also lowers the overall communication cost significantly. Finally, we perform a detailed experimental analysis of our algorithm. Our results indicate that the algorithm compares favorably with the length of the schedule produced by other natural and efficient parallel algorithms proposed in the literature [S. Pautz, An Algorithm for parallel S n sweeps on unstructured meshes, Nucl. Sci. Eng. 140 (2002) 111–136; S. Plimpton, B. Hendrickson, S. Burns, W. McLendon, Parallel algorithms for radiation transport on unstructured grids, Super Comput. (2001)].
5246711
Dependent rounding in bipartite graphs
We combine the pipage rounding technique of Ageev & Sviridenko with a recent rounding method developed by Srinivasan (2001), to develop a new randomized rounding approach for fractional vectors defined on the edge-sets of bipartite graphs. We show various ways of combining this technique with other ideas, leading to the following applications: richer random-graph models for graphs with a given degree-sequence; improved approximation algorithms for: (i) throughput-maximization in broadcast scheduling, (ii) delay-minimization in broadcast scheduling, and (iii) capacitated vertex cover; fair scheduling of jobs on unrelated parallel machines. A useful feature of our method is that it lets us prove certain (probabilistic) per-user fairness properties.
6168494
Approximation algorithms for scheduling on multiple machines
We develop a single rounding algorithm for scheduling on unrelated parallel machines; this algorithm works well with the known linear programming, quadratic programming, and convex programming-relaxations for scheduling to minimize completion time, makespan, and other well-studied objective functions. We obtain the following applications for the general setting of unrelated parallel machines: (i) a bicriteria algorithm for a schedule whose weighted completion-time and makespan simultaneously exhibit the current-best individual approximations for these criteria (3/2 and 2, respectively); (ii) better-than-two approximation guarantees for scheduling under the L/sub p/ norm for all 1 < p < /spl infin/, improving on the 2-approximation algorithms of Azar & Epstein; and (iii) the first constant-factor multicriteria approximation algorithms that handle the weighted completion-time and any given collection of integer L/sub p/ norms. Our algorithm yields a common generalization of rounding theorems due to Karp et al and Shmoys & Tardos; among other applications, this yields an improved approximation for scheduling with resource-dependent processing times studied by Grigoriev et al.
38425944
Scheduling on Unrelated Machines Under Tree-Like Precedence Constraints
We present polylogarithmic approximations for the R|prec|Cmax and R|prec|∑jwjCj problems, when the precedence constraints are “treelike” – i.e., when the undirected graph underlying the precedences is a forest. We also obtain improved bounds for the weighted completion time and flow time for the case of chains with restricted assignment – this generalizes the job shop problem to these objective functions. We use the same lower bound of “congestion+dilation”, as in other job shop scheduling approaches. The first step in our algorithm for the R|prec|Cmax problem with treelike precedences involves using the algorithm of Lenstra, Shmoys and Tardos to obtain a processor assignment with the congestion + dilation value within a constant factor of the optimal. We then show how to generalize the random delays technique of Leighton, Maggs and Rao to the case of trees. For the weighted completion time, we show a certain type of reduction to the makespan problem, which dovetails well with the lower bound we employ for the makespan problem. For the special case of chains, we show a dependent rounding technique which leads to improved bounds on the weighted completion time and new bicriteria bounds for the flow time.
14773410
Algorithmic aspects of capacity in wireless networks
This paper considers two inter-related questions: (i) Given a wireless ad-hoc network and a collection of source-destination pairs {(si,ti)}, what is the maximum throughput capacity of the network, i.e. the rate at which data from the sources to their corresponding destinations can be transferred in the network? (ii) Can network protocols be designed that jointly route the packets and schedule transmissions at rates close to the maximum throughput capacity? Much of the earlier work focused on random instances and proved analytical lower and upper bounds on the maximum throughput capacity. Here, in contrast, we consider arbitrary wireless networks. Further, we study the algorithmic aspects of the above questions: the goal is to design provably good algorithms for arbitrary instances. We develop analytical performance evaluation models and distributed algorithms for routing and scheduling which incorporate fairness, energy and dilation (path-length) requirements and provide a unified framework for utilizing the network close to its maximum throughput capacity.Motivated by certain popular wireless protocols used in practice, we also explore "shortest-path like" path selection strategies which maximize the network throughput. The theoretical results naturally suggest an interesting class of congestion aware link metrics which can be directly plugged into several existing routing protocols such as AODV, DSR, etc. We complement the theoretical analysis with extensive simulations. The results indicate that routes obtained using our congestion aware link metrics consistently yield higher throughput than hop-count based shortest path metrics.
38873931
Distributions on level-sets with applications to approximation algorithms
We consider a family of distributions on fixed-weight vectors in {0, 1}/sup t/; these distributions enjoy certain negative correlation properties and also satisfy pre-specified conditions on their marginal distributions. We show the existence of such families, and present a linear-time algorithm to sample from them. This yields improved approximation algorithms for the following problems: (a) low-congestion multi-path routing; (b) maximum coverage versions of set cover; (c) partial vertex cover problems for bounded-degree graphs; and (d) the Group Steiner Tree problem. For (a) and (b), the improvement is in the approximation ratio; for (c), we show how to speedup existing approximation algorithms while preserving the best-known approximation ratio; we also improve the approximation ratio for certain families of instances of unbounded degree. For (d), we derive an approximation algorithm whose approximation guarantee is at least as good as what is known; our algorithm is shown to have a better approximation guarantee for the worst known input families for existing algorithms.
83148
Latency tolerance through parallelization of time in scientific applications
Summary form only given. Distributed computing environments, such as the grid, promise enormous raw computational power, but involve high communication overheads. It is therefore considered that they are ideally suited for "embarrassingly parallel" applications, such as Monte Carlo, and for certain applications where the loosely-coupled nature of the science involved in the simulations leads to a coarse grained computation. In a typical application, this is not feasible. We discuss our solution strategy, based on scalable functional decomposition, which can be used to keep the computation coarse grained, even on a large number of processors. Such decomposition can be attempted through a variety of means. We discuss the use of time parallelization to achieve this. We demonstrate results with a model problem, and then discuss its implementation for an important problem in nanomaterials simulation. We also show that this technique can be extended to make it inherently fault-tolerant.
15562468
Low discrepancy sets yield approximate min-wise independent permutation families
Motivated by a problem of filtering near-duplicate Web documents, Broder, Charikar, Frieze and Mitzenmacher defined the following notion of ϵ-approximate min-wise independent permutation families. A multiset F of permutations of {0,1,…,n−1} is such a family if for all K⫅{0,1,…,n−1} and any x∈K, a permutation π chosen uniformly at random from F satisfies 
|Pr[min{π(K)}=π(x)]−1|K||≤ϵ|K|. 
We show connections of such families with low discrepancy sets for geometric rectangles, and give explicit constructions of such families F of size nO(logn) for ϵ=1/nΘ(1), improving upon the previously best-known bound of Indyk. We also present polynomial-size constructions when the min-wise condition is required only for |K|≤2O(log2/3n), with ϵ≥2−O(log2/3n).
1401764
New approaches to covering and packing problems
Covering and packing integer programs model a large family of combinatorial optimization problems. The current-best approximation algorithms for these are an instance of the basic probabilistic method: showing that a certain randomized approach produces a good approximation with positive probability. This approach seems inherently sequential; by employing the method of alteration we present the first RNC and NC approximation algorithms that match the best sequential guarantees. Extending our approach, we get the first RNC and NC approximation algorithms for certain multi-criteria versions of these problems. We also present the first NC algorithms for two packing and covering problems that are not subsumed by the above result: finding large independent sets in graphs, and rounding fractional Group Steiner solutions on trees.
36642411
Parameterizing parallel multiplicative lagged-Fibonacci generators
Monte Carlo computations are commonly considered to be naturally parallel. However, one needs to exercise care in parallelizing the underlying pseudorandom number generator (PRNG) to avoid correlations within, and between, random number streams. PRNGs are normally parallelized using one of the following two paradigms: (i) cycle division and (ii) parameterization. Most of the popular PRNGs based on linear recurrences, such as linear congruential generators (LCGs), generalized feedback shift-register generators (GFSRs), and additive lagged-Fibonacci generators (ALFGs) have been parallelized using both these paradigms. While the (nonlinear) multiplicative lagged-Fibonacci generators (MLFG) is considered superior to the ALFG in quality, it had so far been parallelized only via the cycle division paradigm, which has its limitations. In this paper, we describe parallelization of the MLFG using parameterization, and discuss its implementation in the Scalable Parallel Random Number Generators (SPRNG) [ACM Trans. Math. Software 26 (2000) 436] parallel pseudorandom number generation software. We also present empirical results demonstrating the quality, and quantitatively compare the parallel ALFGs and MLFGs quality.