136,464 research outputs found
Next generation software environments : principles, problems, and research directions
The past decade has seen a burgeoning of research and development in software environments. Conferences have been devoted to the topic of practical environments, journal papers produced, and commercial systems sold. Given all the activity, one might expect a great deal of consensus on issues, approaches, and techniques. This is not the case, however. Indeed, the term "environment" is still used in a variety of conflicting ways. Nevertheless substantial progress has been made and we are at least nearing consensus on many critical issues.The purpose of this paper is to characterize environments, describe several important principles that have emerged in the last decade or so, note current open problems, and describe some approaches to these problems, with particular emphasis on the activities of one large-scale research program, the Arcadia project. Consideration is also given to two related topics: empirical evaluation and technology transition. That is, how can environments and their constituents be evaluated, and how can new developments be moved effectively into the production sector
Synapse: Synthetic Application Profiler and Emulator
We introduce Synapse motivated by the needs to estimate and emulate workload
execution characteristics on high-performance and distributed heterogeneous
resources. Synapse has a platform independent application profiler, and the
ability to emulate profiled workloads on a variety of heterogeneous resources.
Synapse is used as a proxy application (or "representative application") for
real workloads, with the added advantage that it can be tuned at arbitrary
levels of granularity in ways that are simply not possible using real
applications. Experiments show that automated profiling using Synapse
represents application characteristics with high fidelity. Emulation using
Synapse can reproduce the application behavior in the original runtime
environment, as well as reproducing properties when used in a different
run-time environments
Lessons Learned from a Decade of Providing Interactive, On-Demand High Performance Computing to Scientists and Engineers
For decades, the use of HPC systems was limited to those in the physical
sciences who had mastered their domain in conjunction with a deep understanding
of HPC architectures and algorithms. During these same decades, consumer
computing device advances produced tablets and smartphones that allow millions
of children to interactively develop and share code projects across the globe.
As the HPC community faces the challenges associated with guiding researchers
from disciplines using high productivity interactive tools to effective use of
HPC systems, it seems appropriate to revisit the assumptions surrounding the
necessary skills required for access to large computational systems. For over a
decade, MIT Lincoln Laboratory has been supporting interactive, on-demand high
performance computing by seamlessly integrating familiar high productivity
tools to provide users with an increased number of design turns, rapid
prototyping capability, and faster time to insight. In this paper, we discuss
the lessons learned while supporting interactive, on-demand high performance
computing from the perspectives of the users and the team supporting the users
and the system. Building on these lessons, we present an overview of current
needs and the technical solutions we are building to lower the barrier to entry
for new users from the humanities, social, and biological sciences.Comment: 15 pages, 3 figures, First Workshop on Interactive High Performance
Computing (WIHPC) 2018 held in conjunction with ISC High Performance 2018 in
Frankfurt, German
CloudHealth: A Model-Driven Approach to Watch the Health of Cloud Services
Cloud systems are complex and large systems where services provided by
different operators must coexist and eventually cooperate. In such a complex
environment, controlling the health of both the whole environment and the
individual services is extremely important to timely and effectively react to
misbehaviours, unexpected events, and failures. Although there are solutions to
monitor cloud systems at different granularity levels, how to relate the many
KPIs that can be collected about the health of the system and how health
information can be properly reported to operators are open questions. This
paper reports the early results we achieved in the challenge of monitoring the
health of cloud systems. In particular we present CloudHealth, a model-based
health monitoring approach that can be used by operators to watch specific
quality attributes. The CloudHealth Monitoring Model describes how to
operationalize high level monitoring goals by dividing them into subgoals,
deriving metrics for the subgoals, and using probes to collect the metrics. We
use the CloudHealth Monitoring Model to control the probes that must be
deployed on the target system, the KPIs that are dynamically collected, and the
visualization of the data in dashboards.Comment: 8 pages, 2 figures, 1 tabl
The Reality of Measuring Human Service Programs: Results of a Survey
In the summer of 2013, Idealware created and distributed a survey to learn how human service organizations from their own mailing list are actually using technology to measure and evaluate the outcomes of their programs. The suvey looked at a general overview of outcomes measurement and program evaluation topics, from how frequently they look at data and how much time they spend doing so to what types of metrics the organizations were tracking. To further understand the realities of measuring program effectiveness, Idealware conducted a site visit and interview of three human service organizations in Portland, Maine. The results clearly show that the respondents are struggling to measure their programs
TANGO: Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation
The paper is concerned with the issue of how software systems actually use
Heterogeneous Parallel Architectures (HPAs), with the goal of optimizing power
consumption on these resources. It argues the need for novel methods and tools
to support software developers aiming to optimise power consumption resulting
from designing, developing, deploying and running software on HPAs, while
maintaining other quality aspects of software to adequate and agreed levels. To
do so, a reference architecture to support energy efficiency at application
construction, deployment, and operation is discussed, as well as its
implementation and evaluation plans.Comment: Part of the Program Transformation for Programmability in
Heterogeneous Architectures (PROHA) workshop, Barcelona, Spain, 12th March
2016, 7 pages, LaTeX, 3 PNG figure
Soft peer review: social software and distributed scientific evaluation
The debate on the prospects of peer-review in the Internet age and the
increasing criticism leveled against the dominant role of impact factor
indicators are calling for new measurable criteria to assess scientific quality.
Usage-based metrics offer a new avenue to scientific quality assessment but
face the same risks as first generation search engines that used unreliable
metrics (such as raw traffic data) to estimate content quality. In this article I
analyze the contribution that social bookmarking systems can provide to the
problem of usage-based metrics for scientific evaluation. I suggest that
collaboratively aggregated metadata may help fill the gap between traditional
citation-based criteria and raw usage factors. I submit that bottom-up,
distributed evaluation models such as those afforded by social bookmarking
will challenge more traditional quality assessment models in terms of coverage,
efficiency and scalability. Services aggregating user-related quality indicators
for online scientific content will come to occupy a key function in the scholarly
communication system
When situativity meets objectivity in peer-production of knowledge:the case of the WikiRate platform
PurposeThe purpose of this paper is to further the debate on Knowledge Artefacts (KAs), by presenting the design of WikiRate, a Collective Awareness platform whose goal is to support a wider public contributing to the generation of knowledge on environmental, social and governance (ESG) performance of companies.Design/methodology/approachThe material presented in the paper comes from the first-hand experience of the authors as part of the WikiRate design team. This material is reflexively discussed using concepts from the field of science and technology studies.FindingsUsing the concept of the “funnel of interest”, the authors discuss how the design of a KA like WikiRate relies on the designers’ capacity to translate general statements into particular design solutions. The authors also show how this funnelling helps understanding the interplay between situativity and objectivity in a KA. The authors show how WikiRate is a peer-production platform based on situativity, which requires a robust level of objectivity for producing reliable knowledge about the ESG performance of companies.Originality/valueThis paper furthers the debate on KAs. It presents a relevant design example and offers in the discussion a set of design and community building recommendations to practitioners
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