115,369 research outputs found
Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnections
Cortical synapse organization supports a range of dynamic states on multiple
spatial and temporal scales, from synchronous slow wave activity (SWA),
characteristic of deep sleep or anesthesia, to fluctuating, asynchronous
activity during wakefulness (AW). Such dynamic diversity poses a challenge for
producing efficient large-scale simulations that embody realistic metaphors of
short- and long-range synaptic connectivity. In fact, during SWA and AW
different spatial extents of the cortical tissue are active in a given timespan
and at different firing rates, which implies a wide variety of loads of local
computation and communication. A balanced evaluation of simulation performance
and robustness should therefore include tests of a variety of cortical dynamic
states. Here, we demonstrate performance scaling of our proprietary Distributed
and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and
AW for bidimensional grids of neural populations, which reflects the modular
organization of the cortex. We explored networks up to 192x192 modules, each
composed of 1250 integrate-and-fire neurons with spike-frequency adaptation,
and exponentially decaying inter-modular synaptic connectivity with varying
spatial decay constant. For the largest networks the total number of synapses
was over 70 billion. The execution platform included up to 64 dual-socket
nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40GHz
clock rates. Network initialization time, memory usage, and execution time
showed good scaling performances from 1 to 1024 processes, implemented using
the standard Message Passing Interface (MPI) protocol. We achieved simulation
speeds of between 2.3x10^9 and 4.1x10^9 synaptic events per second for both
cortical states in the explored range of inter-modular interconnections.Comment: 22 pages, 9 figures, 4 table
Scaling of a large-scale simulation of synchronous slow-wave and asynchronous awake-like activity of a cortical model with long-range interconnections
Cortical synapse organization supports a range of dynamic states on multiple
spatial and temporal scales, from synchronous slow wave activity (SWA),
characteristic of deep sleep or anesthesia, to fluctuating, asynchronous
activity during wakefulness (AW). Such dynamic diversity poses a challenge for
producing efficient large-scale simulations that embody realistic metaphors of
short- and long-range synaptic connectivity. In fact, during SWA and AW
different spatial extents of the cortical tissue are active in a given timespan
and at different firing rates, which implies a wide variety of loads of local
computation and communication. A balanced evaluation of simulation performance
and robustness should therefore include tests of a variety of cortical dynamic
states. Here, we demonstrate performance scaling of our proprietary Distributed
and Plastic Spiking Neural Networks (DPSNN) simulation engine in both SWA and
AW for bidimensional grids of neural populations, which reflects the modular
organization of the cortex. We explored networks up to 192x192 modules, each
composed of 1250 integrate-and-fire neurons with spike-frequency adaptation,
and exponentially decaying inter-modular synaptic connectivity with varying
spatial decay constant. For the largest networks the total number of synapses
was over 70 billion. The execution platform included up to 64 dual-socket
nodes, each socket mounting 8 Intel Xeon Haswell processor cores @ 2.40GHz
clock rates. Network initialization time, memory usage, and execution time
showed good scaling performances from 1 to 1024 processes, implemented using
the standard Message Passing Interface (MPI) protocol. We achieved simulation
speeds of between 2.3x10^9 and 4.1x10^9 synaptic events per second for both
cortical states in the explored range of inter-modular interconnections.Comment: 22 pages, 9 figures, 4 table
Identifying and Modelling Complex Workflow Requirements in Web Applications
Workflow plays a major role in nowadays business and therefore its
requirement elicitation must be accurate and clear for achieving the solution
closest to business’s needs. Due to Web applications popularity, the Web is becoming
the standard platform for implementing business workflows. In this
context, Web applications and their workflows must be adapted to market demands
in such a way that time and effort are minimize. As they get more popular,
they must give support to different functional requirements but also they
contain tangled and scattered behaviour. In this work we present a model-driven
approach for modelling workflows using a Domain Specific Language for Web
application requirement called WebSpec. We present an extension to WebSpec
based on Pattern Specifications for modelling crosscutting workflow requirements
identifying tangled and scattered behaviour and reducing inconsistencies
early in the cycle
Preparing for Climate Impacts: Lessons from the Front Lines
In a synthesis report to The Kresge Foundation, the Georgetown Climate Center shares lessons learned from its adaptation work in recent years. The report includes short case studies highlighting successful efforts as well as barriers to change
Supporting evidence-based adaptation decision-making in Victoria: a synthesis of climate change adaptation research
This research synthesis provides policy-makers and practitioners with an understanding of the building blocks for effective adaptation decision-making, as evidenced through the NCCARF research program. It synthesised a portfolio of adaptation research for each Australian state and territory and addressing the complex relationships between research and policy development. Each state and territory synthesis report directs users to research relevant identified priorities
Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches
Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements
Making space for proactive adaptation of rapidly changing coasts: a windows of opportunity approach
Coastlines are very often places where the impacts of global change are felt most keenly,
and they are also often sites of high values and intense use for industry, human habitation, nature
conservation and recreation. In many countries, coastlines are a key contested territory for planning
for climate change, and also locations where development and conservation conflicts play out. As
a “test bed” for climate change adaptation, coastal regions provide valuable, but highly diverse
experiences and lessons. This paper sets out to explore the lessons of coastal planning and
development for the implementation of proactive adaptation, and the possibility to move from
adaptation visions to actual adaptation governance and planning. Using qualitative analysis of
interviews and workshops, we first examine what the barriers are to proactive adaptation at the coast,
and how current policy and practice frames are leading to avoidable lock-ins and other maladaptive
decisions that are narrowing our adaptation options. Using examples from UK, we then identify
adaptation windows that can be opened, reframed or transformed to set the course for proactive
adaptation which links high level top-down legislative requirements with local bottom-up actions.
We explore how these windows can be harnessed so that space for proactive adaptation increases
and maladaptive decisions are reduced
Staying on Track from Paris: Advancing the Key Elements of the Paris Agreement
The Paris Agreement adopted in December 2015 provides essential building blocks for universal action to address climate change. Now, much work is needed to breathe life into the provisions and commitments of the Agreement in order to realize the globally agreed vision to limit temperature rise, build the ability to adapt to climate impacts, and align financial flows toward zerocarbon and climate-resilient development. The Parties to the United Nations Framework Convention on Climate Change (UNFCCC) must continue to cooperate effectively to unpack and clarify the key tasks and activities outlined in the Agreement in order to provide a well-defined pathway to implementation. This paper takes an in-depth look at the Paris Agreement, highlighting important outcomes and the tasks and activities that now need to be undertaken to elaborate and develop the critical rules and processes under the Agreement. Ensuring that these rules and processes are strong and effective will be essential to promoting ambitious climate action and accelerating it in the coming years
Adaptive Process Management in Cyber-Physical Domains
The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
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