110,748 research outputs found
Optimal processor assignment for pipeline computations
The availability of large scale multitasked parallel architectures introduces the following processor assignment problem for pipelined computations. Given a set of tasks and their precedence constraints, along with their experimentally determined individual responses times for different processor sizes, find an assignment of processor to tasks. Two objectives are of interest: minimal response given a throughput requirement, and maximal throughput given a response time requirement. These assignment problems differ considerably from the classical mapping problem in which several tasks share a processor; instead, it is assumed that a large number of processors are to be assigned to a relatively small number of tasks. Efficient assignment algorithms were developed for different classes of task structures. For a p processor system and a series parallel precedence graph with n constituent tasks, an O(np2) algorithm is provided that finds the optimal assignment for the response time optimization problem; it was found that the assignment optimizing the constrained throughput in O(np2log p) time. Special cases of linear, independent, and tree graphs are also considered
A2THOS: Availability Analysis and Optimisation in SLAs
IT service availability is at the core of customer satisfaction and business success for todayâs organisations. Many medium-large size organisations outsource part of their IT services to external providers, with Service Level Agreements describing the agreed availability of outsourced service components. Availability management of partially outsourced IT services is a non trivial task since classic approaches for calculating availability are not applicable, and IT managers can only rely on their expertise to fulfil it. This often leads to the adoption of non optimal solutions. In this paper we present A2THOS, a framework to calculate the availability of partially outsourced IT services in the presence of SLAs and to achieve a cost-optimal choice of availability levels for outsourced IT components while guaranteeing a target availability level for the service
A Parallel Adaptive P3M code with Hierarchical Particle Reordering
We discuss the design and implementation of HYDRA_OMP a parallel
implementation of the Smoothed Particle Hydrodynamics-Adaptive P3M (SPH-AP3M)
code HYDRA. The code is designed primarily for conducting cosmological
hydrodynamic simulations and is written in Fortran77+OpenMP. A number of
optimizations for RISC processors and SMP-NUMA architectures have been
implemented, the most important optimization being hierarchical reordering of
particles within chaining cells, which greatly improves data locality thereby
removing the cache misses typically associated with linked lists. Parallel
scaling is good, with a minimum parallel scaling of 73% achieved on 32 nodes
for a variety of modern SMP architectures. We give performance data in terms of
the number of particle updates per second, which is a more useful performance
metric than raw MFlops. A basic version of the code will be made available to
the community in the near future.Comment: 34 pages, 12 figures, accepted for publication in Computer Physics
Communication
An ant colony algorithm for the sequential testing problem under precedence constraints.
We consider the problem of minimum cost sequential
testing of a series (parallel) system under precedence
constraints that can be modeled as a nonlinear integer program.
We develop and implement an ant colony algorithm for the
problem. We demonstrate the performance of this algorithm
for special type of instances for which the optimal solutions
can be found in polynomial time. In addition, we compare the
performance of the algorithm with a special branch and bound
algorithm for general instances. The ant colony algorithm is
shown to be particularly effective for larger instances of the
problem
A Survey on Array Storage, Query Languages, and Systems
Since scientific investigation is one of the most important providers of
massive amounts of ordered data, there is a renewed interest in array data
processing in the context of Big Data. To the best of our knowledge, a unified
resource that summarizes and analyzes array processing research over its long
existence is currently missing. In this survey, we provide a guide for past,
present, and future research in array processing. The survey is organized along
three main topics. Array storage discusses all the aspects related to array
partitioning into chunks. The identification of a reduced set of array
operators to form the foundation for an array query language is analyzed across
multiple such proposals. Lastly, we survey real systems for array processing.
The result is a thorough survey on array data storage and processing that
should be consulted by anyone interested in this research topic, independent of
experience level. The survey is not complete though. We greatly appreciate
pointers towards any work we might have forgotten to mention.Comment: 44 page
Formal Representation of the SS-DB Benchmark and Experimental Evaluation in EXTASCID
Evaluating the performance of scientific data processing systems is a
difficult task considering the plethora of application-specific solutions
available in this landscape and the lack of a generally-accepted benchmark. The
dual structure of scientific data coupled with the complex nature of processing
complicate the evaluation procedure further. SS-DB is the first attempt to
define a general benchmark for complex scientific processing over raw and
derived data. It fails to draw sufficient attention though because of the
ambiguous plain language specification and the extraordinary SciDB results. In
this paper, we remedy the shortcomings of the original SS-DB specification by
providing a formal representation in terms of ArrayQL algebra operators and
ArrayQL/SciQL constructs. These are the first formal representations of the
SS-DB benchmark. Starting from the formal representation, we give a reference
implementation and present benchmark results in EXTASCID, a novel system for
scientific data processing. EXTASCID is complete in providing native support
both for array and relational data and extensible in executing any user code
inside the system by the means of a configurable metaoperator. These features
result in an order of magnitude improvement over SciDB at data loading,
extracting derived data, and operations over derived data.Comment: 32 pages, 3 figure
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