An Efficient Data Dependence Analysis for Parallelizing Compilers
A novel algorithm, called the lambda test, is presented for an efficient and accurate data dependence analysis of multidimensional array references. It extends the numerical methods to allow all dimensions of array references to be tested simultaneously. Hence, it combines the efficiency and the accuracy of both approaches. This algorithm has been implemented in Parafrase, a Fortran program parallelization restructurer developed at the University of Illinois at Urbana-Champaign. Some experimental results are presented to show its effectiveness.

title: A theoretical foundation for program transformations to reduce cache thrashing due to true data sharing
abstract: Cache thrashing due to true data sharing can degrade the performance of parallel programs significantly. Our previous work showed that parallel task alignment via program transformations can be quite effective for the reduction of such cache thrashing. In this paper, we present a theoretical foundation for such program transformations. Based on linear algebra and the theory of numbers, our work analyzes the data dependences among the tasks created by a fork-join parallel program and determines at compile time how these tasks should be assigned to processors in order to reduce cache thrashing due to true data sharing. Our analysis and program transformations can be easily performed by compilers for parallel computers.

title: Experience in the Automatic Parallelization of Four Perfect-Benchmark Programs
abstract: This paper discusses the techniques used to hand-parallelize, for the Alliant FX/80, four Fortran programs from the Perfect-Benchmark suite. The paper also includes the execution times of the programs before and after the transformations. The four programs considered here were not effectively parallelized by the automatic translators available to the authors. However, most of the techniques used for hand parallelization, and perhaps all of them, have wide applicability and can be incorporated into existing translators.

title: New tiling techniques to improve cache temporal locality
abstract: Tiling is a well-known loop transformation to improve temporal locality of nested loops. Current compiler algorithms for tiling are limited to loops which are perfectly nested or can be transformed, in trivial ways, into a perfect nest. This paper presents a number of program transformations to enable tiling for a class of nontrivial imperfectly-nested loops such that cache locality is improved. We define a program model for such loops and develop compiler algorithms for their tiling. We propose to adopt odd-even variable duplication to break anti- and output dependences without unduly increasing the working-set size, and to adopt speculative execution to enable tiling of loops which may terminate prematurely due to, e.g. convergence tests in iterative algorithms. We have implemented these techniques in a research compiler, Panorama. Initial experiments with several benchmark programs are performed on SGI workstations based on MIPS R5K and R10K processors. Overall, the transformed programs run faster by 9% to 164%.

title: Compiler algorithms for event variable synchronization
abstract: Event variable synchronization is a well known mecha nism for enforcing data dependences in a program that runs in parallel on a shared memory multiprocessor This paper presents compiler algorithms to automati cally generate event variable synchronization code Pre viously published algorithms dealt with single parallel loops in which dependence distances are constant and known by the compiler However loops in real appli cation programs are often arbitrarily nested Moreover compilers are often unable to determine dependence dis tances In contrast our algorithms generate synchro nization code based directly on array subscripts and do not require constant distances in data dependences The algorithms are designed for arbitrarily nested loops in cluding triangular or trapezoidal loops

title: On Reducing Data Synchronization in Multiprocessed Loops
abstract: In this correspondence we present and prove the correctness of an algorithm for reducing the number of synchronized memory references to shared data elements in multiprocessed loops. Optimizing compilers for shared memory multiprocessors can use this algorithm to reduce synchronization overhead. The algorithm has been implemented as a new module in the multiprocessors version of Parafrase, the restructuring system of the University of Illinois. We present a brief discussion of experiments we performed to asses the effectiveness of this algorithm in reducing the synchronization overhead for the 61 subroutines of EISPACK, a package for computing matrix eigenvectors and eigenvalues.

title: A divide-and-conquer 2.5-D floorplanning algorithm based on statistical wirelength estimation
abstract: An efficient and effective divide-and conquer 2.5D floorplanning algorithm is proposed for wirelength optimization. Modules are pre-partitioned into different dies with respect to the statistical wirelength estimation result. Then a floorplan is generated on each die for wirelength optimization. The new partitioning method successfully solves the conflict between wirelength minimization and inter-die via constraints. Experimental results show that our algorithm could provide noticeable improvement in the total wirelength compared to both 2D design and the previous 2.5D floorplanning algorithm.

title: C-Miner: Mining Block Correlations in Storage Systems
abstract: Block correlations are common semantic patterns in storage systems. These correlations can be exploited for improving the effectiveness of storage caching, prefetching, data layout and disk scheduling. Unfortunately, information about block correlations is not available at the storage system level. Previous approaches for discovering file correlations in file systems do not scale well enough to be used for discovering block correlations in storage systems. 
 
In this paper, we propose C-Miner, an algorithm which uses a data mining technique called frequent sequence mining to discover block correlations in storage systems. C-Miner runs reasonably fast with feasible space requirement, indicating that it is a practical tool for dynamically inferring correlations in a storage system. Moreover, we have also evaluated the benefits of block correlation-directed prefetching and data layout through experiments. Our results using real system workloads show that correlation-directed prefetching and data layout can reduce average I/O response time by 12-25% compared to the base case, and 7-20% compared to the commonly used sequential prefetching scheme.

title: Rational Solutions of Riccati-like Partial Differential Equations
abstract: When factoring linear partial differential systems with a finite-dimensional solution space or analysing symmetries of nonlinear ODEs, we need to look for rational solutions of certain nonlinear PDEs. The nonlinear PDEs are called Riccati-like because they arise in a similar way as Riccati ODEs. In this paper we describe the structure of rational solutions of a Riccati-like system, and an algorithm for computing them. The algorithm is also applicable to finding all rational solutions of Lie?s system { ?xu+u2+a1u+a2v+a3, ?yu+uv+b1u+b2v+b3, ?xv+uv+c1u+c2v+c3, ?yv+v2+d1u+d2v+d3},where a1, . . . , d3are rational functions of x and y.

title: An Efficient Sort-Based DDM Matching Algorithm for HLA Applications with a Large Spatial Environment
abstract: Simulation is a low cost and safe alternative to solve complex problems in various areas. To promote reuse and interoperability of simulation applications and link geographically dispersed simulation components, distributed simulation was introduced. The high level architecture (HLA) is the IEEE standard for distributed simulation. To optimize communication efficiency between simulation components, HLA defines a data distribution management (DDM) service group for filtering out unnecessary data exchange. It relies on the computation of overlap between update and subscription regions, which is called matching. In this paper, we propose an efficient sort-based DDM matching algorithm for HLA applications with a large spatial environment. A theoretical analysis of our algorithm concludes that it should have good storage and computational scalability. The experimental results have verified the theoretical conclusions by showing that our algorithm has much less storage requirement than the original sort-based matching algorithm and generally has the best computational performance when compared with region-based and the original sort-based matching algorithms.

title: An Object-Oriented Approach Using a Top-Down and Bottom-Up Process for Manipulative Action Recognition
abstract: Different from many gesture-based human-robot interaction applications, which focused on the recognition of the interactional or the pointing gestures, this paper proposes a vision-based method for manipulative gesture recognition aiming to achieve natural, proactive, and non-intrusive interaction between humans and robots. The main contributions of the paper are an object-centered scheme for the segmentation and characterization of hand trajectory information, the use of particle filtering methods for an action primitive spotting, and the tight coupling of bottom-up and top-down processing that realizes a task-driven attention filter for low-level recognition steps. In contrast to purely trajectory based techniques, the presented approach is called object-oriented w.r.t. two different aspects: it is object-centered in terms of trajectory features that are defined relative to an object, and it uses object-specific models for action primitives. The system has a two-layer structure recognizing both the HMM-modeled manipulative primitives and the underlying task characterized by the manipulative primitive sequence. The proposed top-down and bottom-up mechanism between the two layers decreases the image processing load and improves the recognition rate.