Effective early termination techniques for text similarity join operator

Bu çalışma, 26-28 Ekim 2005 tarihleri arasında İstanbul[Türkiye]'da düzenlenen 20. International Symposium on Computer and Information Sciences'da bildiri olarak sunulmuştur.Text similarity join operator joins two relations if their join attributes are textually similar to each other, and it has a variety of application domains including integration and querying of data from heterogeneous resources; cleansing of data; and mining of data. Although, the text similarity join operator is widely used, its processing is expensive due to the huge number of similarity computations performed. In this paper, we incorporate some short cut evaluation techniques from the Information Retrieval domain, namely Harman, quit, continue, and maximal similarity filter heuristics, into the previously proposed text similarity join algorithms to reduce the amount of similarity computations needed during the join operation. We experimentally evaluate the original and the heuristic based similarity join algorithms using real data obtained from the DBLP Bibliography database, and observe performance improvements with continue and maximal similarity filter heuristics.Inst Elec & Elect Engineers, Turkey SectBoğaziçi Üniversites

Resource Bartering in Data Grids

We present models for bartering of resources on grids. Bartering models can be useful for making resource allocation decisions in grids and perhaps even for building a so called barter grid whereby distributed resources such as electronic media can be bartered. Grids allow various resources to be shared among many users. This sharing however definitely does not mean that everyone will have unrestricted use of the resources. Some mechanism such as pricing or quotas can be employed in order to enforce controlled sharing of resources. A barter model for resource sharing can enable people or computer centers to directly get something in return for letting their resources to be used by others. We utilize directed hypergraphs to develop a barter model in which multiple resources can be traded. We prove that the decision version of the multi-resource bartering problem is NP-complete. We present an integer programming formulation for the bartering problem. We also present a linear time algorithm to compute components that may contain feasible bartering solutions. We generalize our multi-resource bartering formulation to the case where multiple instances of resources are present. Finally, we present various computational results from our software that makes use of LP_SOLVE and CPLEX mixed integer programming libraries to solve example bartering problems

Extending SLURM with Support for GPU Ranges

SLURM resource management system is used on many TOP500 supercomputers. In this work, we present enhancements that we added to our AUCSCHED heterogeneous CPU-GPU scheduler plug-in whose rst version was released in December 2012. In this new version, called AUCSCHED2, two enhancements are contributed: The rst is the extension of SLURM to support GPU ranges. The current version of SLURM supports speci cation of node range but not of GPU ranges. Such a feature can be very useful to runtime auto-tuning applications and systems that can make use of variable number of GPUs. The second enhancement involves the implementation of a new integer programming formulation in AUCSCHED2 that drastically reduces the number of variables. This allows faster solution and larger number of bids to be generated. SLURM emulation results are presented for the heterogeneous 1408 node Tsubame supercomputer which has 12 cores and 3 GPU's on each of its nodes. AUCSCHED2 is available at http://code.google.com/p/slurm-ipsched/

Worst Case Complexity of Parallel Triangular Mesh Refinement by Longest Edge Bisection

We present a logarithmic algorithm for performing parallel refinement of triangular meshes by the widely used longest edge bisection procedure. We show that the refinement propagation forms a data dependency which can be expressed as a forest of directed trees. We solve a parallel Euler Tour problem on the trees to propagate the refinement. After propagation, we apply renement templates. Our algorithm improves earlier reported results which had linear worst case complexity

Compiler Technology for Parallel Scientific Computation

There is a need for compiler technology that, given the source program, will generate efficient parallel codes for different architectures with minimal user involvement. Parallel computation is becoming indispensable in solving large-scale problems in science and engineering. Yet, the use of parallel computation is limited by the high costs of developing the needed software. To overcome this difficulty we advocate a comprehensive approach to the development of scalable architecture-independent software for scientific computation based on our experience with Equational Programming Language, EPL

Run-time optimization of sparse matrix-vector multiplication on simd machines

Abstract. Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-vector product is computed repeatedly, often thousands of times, with updated values of the vector until convergence is achieved. In an SIMD architecture, each processor has to fetch the updated off-processor vector elements while computing its share of the product. In this paper, we report on run-time optimization of array distribution and offprocessor data fetching to reduce both the communication and computation time. The optimization is applied to a sparse matrix stored in a compressed sparse row-wise format. Actual runs on test matrices produced up to a 35 percent relative improvement over a block distribution with a naive multiplication algorithm while simulations over a wider range of processors indicate that up to a 60 percent improvement may be possible in some cases.

Parallelization of an Object-Oriented Unstructured Aeroacoustics Solver

A computational aeroacoustics code based on the discontinuous Galerkin method is ported to several parallel platforms using MPI. The discontinuous Galerkin method is a compact high-order method that retains its accuracy and robustness on non-smooth unstructured meshes. In its semi-discrete form, the discontinuous Galerkin method can be combined with explicit time marching methods making it well suited to time accurate computations. The compact nature of the discontinuous Galerkin method also makes it well suited for distributed memory parallel platforms. The original serial code was written using an objectoriented approach and was previously optimized for cache-based machines. The port to parallel platforms was achieved simply by treating partition boundaries as a type of boundary condition. Code modifications were minimal because boundary conditions were abstractions in the original program. Scalability results are presented for the SGI Origin, IBM SP2, and clusters of SGI and Sun workstations. Slightly superlinear speedup is achieved on a fixed-size problem on the Origin, due to cache effects