41859107
Preconditioned Conjugate Gradient Solver for Large Sparse Systems on MPI
5025109
Embedding Complete Binary Trees into Butterfly Networks
The authors present embeddings of complete binary trees into butterfly networks with or without wrap-around connections. Let m be an even integer and q=m+(log m)-1. The authors show how to embed a 2/sup q+1/-1-node complete binary tree T(q) into a (m+1)2/sup m+1/-node wrap-around butterfly B/sub w/(m+1) with a dilation of 4, and how to embed T(q) into a (m+2)2/sup m+2/-node wrap-around butterfly B/sub w/(m+2) with an optimal dilation of 2. They also present an embedding of a wrap-around butterfly B/sub w/(m) into a (m+1)2/sup m/-node no-wrap-around butterfly B(m) with a dilation of 3. Using this embedding it is shown that T(q) can be embedded into a no-wrap butterfly B(m+1) (resp. B(m+2)) with a dilation of 8 (resp. 5). >
6027825
Generalized compressed tree machines
Parallel machines interconnecting up to thousands of processors have been proposed and recently built. One of the earliest and the most prominent one is a complete binary tree machine. The authors propose a family of tree machines called generalized compressed tree machines. Generalized compressed tree machines may, in general, be viewed as a derivative of the complete binary tree networks.<<ETX>>
195611449
Scheduling tasks in multiprocessor systems using evolutionary strategies
Scheduling tasks in multiprocessor systems is a difficult problem. The paper describes a method based upon evolutionary strategies (using genetic algorithms) to aid in finding good task assignments. The technique is illustrated by scheduling a digital signal processing algorithm on a two processor distributed system.<<ETX>>
17006088
An Efficient MAP Classifier for Sensornets
The classification phase is computationally intensive and frequently recurs in tracking applications in sensor networks. Most related work uses traditional signal processing classifiers, such as Maximum A Posterior (MAP) classifier. Naive formulations of MAP are not feasible for resource constraint sensornet nodes. In this paper, we study computationally efficient methods for classification. We propose to use one-sided Jacobi iterations for eigen value decomposition of the covariance matrices, the inverse of which are needed in MAP classifier. We show that this technique greatly simplifies the execution of MAP classifier and makes it a feasible and efficient choice for sensornet applications.
35215015
Coarse Grain Preconditioned Conjugate Gradient Solver for Large Sparse Systems
We explore a coarse grain parallel algorithm for the solution of large sparse linear systems with symmetric positive definite matrix, based on a preconditioned conjugate gradient method.
1312822
One Hop Lookups for Peer-to-Peer Overlays
Current peer-to-peer lookup algorithms have been designed with the assumption that routing information at each member node must be kept small, so that the bookkeeping required to respond to system membership changes is also small. In this paper, we show that this assumption is unnecessary, and present a technique that maintains complete routing tables at each node. The technique is able to handle frequent membership changes and scales to large systems having more than a million nodes. The resulting peer-to-peer system is robust and can route lookup queries in just one hop, thus enabling applications that cannot tolerate the delay of multi-hop routing.
14760800
Deciding Separation Logic Formulae by SAT and Incremental Negative Cycle Elimination
Separation logic is a subset of the quantifier-free first order logic. It has been successfully used in the automated verification of systems that have large (or unbounded) integer-valued state variables, such as pipelined processor designs and timed systems. In this paper, we present a fast decision procedure for separation logic, which combines Boolean satisfiability (SAT) with a graph based incremental negative cycle elimination algorithm. Our solver abstracts a separation logic formula into a Boolean formula by replacing each predicate with a Boolean variable. Transitivity constraints over predicates are detected from the constraint graph and added on a need-to basis. Our solver handles Boolean and theory conflicts uniformly at the Boolean level. The graph based algorithm supports not only incremental theory propagation, but also constant time theory backtracking without using a cumbersome history stack. Experimental results on a large set of benchmarks show that our new decision procedure is scalable, and outperforms existing techniques for this logic.
878886
Verification of embedded memory systems using efficient memory modeling
We describe verification techniques for embedded memory systems using efficient memory modeling (EMM), without explicitly modeling each memory bit. We extend our previously proposed approach of EMM in bounded model checking (BMC) for a single read/write port single memory system, to more commonly occurring systems with multiple memories, having multiple read and write ports. More importantly, we augment such EMM to providing correctness proofs, in addition to finding real bugs as before. The novelties of our verification approach are in (a) combining EMM with a proof-based abstraction that preserves the correctness of a property up to a certain analysis depth of SAT-based BMC, and (b) modeling arbitrary initial memory state precisely and thereby providing inductive proofs using SAT-based BMC for embedded memory systems. Similar to the previous approach, we construct a verification model by eliminating memory arrays, but retaining the memory interface signals with their control logic and adding constraints on those signals at every analysis depth to preserve the data forwarding semantics. The size of these EMM constraints depends quadratically on the number of memory accesses and the number of read and write ports; and linearly on the address and data widths and the number of memories. We show the effectiveness of our approach on several industry designs and software programs.
15353920
Beyond safety: customized SAT-based model checking
Model checking of safety properties has taken a significant lead over nonsafety properties in recent years. To bridge the gap, we propose dedicated SAT-based model checking algorithms for properties beyond safety. Previous bounded model checking (BMC) approaches have relied on either converting such properties to safety checking, or finding proofs by deriving termination criteria using loop-free path analysis. Instead, our approach uses a customized SAT-based formulation for bounded model checking of nonsafety properties, and determines the completeness bounds for liveness using unbounded SAT-based analysis. Our main contributions are: 1) Customized property translations for LTL formulas for BMC, with novel features that utilize partitioning, learning, and incremental formulation. Customized translations not only improve the BMC performance significantly in comparison to standard monolithic LTL translations, but also allow efficient derivation and use of completeness bounds. Though we discuss the translation schemas for liveness, they can be easily extended to handle other LTL properties as well. 2) Customized formulations for determining completeness bounds for liveness using SAT-based unbounded model checking (UMC) rather than using loop-free path analysis. These formulations comprise greatest fixed-point and least fixed-point computations to efficiently handle nested properties using SAT-based quantification approaches. We show the effectiveness of our overall approach for checking liveness on public benchmarks and several industry designs.
17115672
Emergent Semantics through Interaction in Image Databases
In this paper, we briefly discuss some aspects of image semantics and the role that it plays for the design of image databases. We argue that images don't have an intrinsic meaning, but that they are endowed with a meaning by placing them in the context of other images and by the user interaction. From this observation, we conclude that, in an image, database users should be allowed to manipulate not only the individual images, but also the relation between them. We present an interface model based on the manipulation of configurations of images.