14,050 research outputs found
SimGrid: a Sustained Effort for the Versatile Simulation of Large Scale Distributed Systems
In this paper we present Simgrid, a toolkit for the versatile simulation of
large scale distributed systems, whose development effort has been sustained
for the last fifteen years. Over this time period SimGrid has evolved from a
one-laboratory project in the U.S. into a scientific instrument developed by an
international collaboration. The keys to making this evolution possible have
been securing of funding, improving the quality of the software, and increasing
the user base. In this paper we describe how we have been able to make advances
on all three fronts, on which we plan to intensify our efforts over the
upcoming years.Comment: 4 pages, submission to WSSSPE'1
Scientific Computing Meets Big Data Technology: An Astronomy Use Case
Scientific analyses commonly compose multiple single-process programs into a
dataflow. An end-to-end dataflow of single-process programs is known as a
many-task application. Typically, tools from the HPC software stack are used to
parallelize these analyses. In this work, we investigate an alternate approach
that uses Apache Spark -- a modern big data platform -- to parallelize
many-task applications. We present Kira, a flexible and distributed astronomy
image processing toolkit using Apache Spark. We then use the Kira toolkit to
implement a Source Extractor application for astronomy images, called Kira SE.
With Kira SE as the use case, we study the programming flexibility, dataflow
richness, scheduling capacity and performance of Apache Spark running on the
EC2 cloud. By exploiting data locality, Kira SE achieves a 2.5x speedup over an
equivalent C program when analyzing a 1TB dataset using 512 cores on the Amazon
EC2 cloud. Furthermore, we show that by leveraging software originally designed
for big data infrastructure, Kira SE achieves competitive performance to the C
implementation running on the NERSC Edison supercomputer. Our experience with
Kira indicates that emerging Big Data platforms such as Apache Spark are a
performant alternative for many-task scientific applications
Co-creation and user innovation: The role of online 3D printing platforms
The aim of this article is to investigate the changes brought about by online 3D printing platforms in co-creation and user innovation. As doing so requires a thorough understanding of the level of user involvement in productive processes and a clear view of the nature of co-creative processes, this article provides a âprosumptionâ framework and a typology of co-creation activities. Then, based on case studies of 22 online 3D printing platforms, a service-based taxonomy of these platforms is constructed. The taxonomy and typology are then matched to investigate the role played by online 3D platforms in regard to the various types of co-creation activities and, consequently, how this impacts user innovation
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