Topic
Workflow
About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.
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TL;DR: This paper uses three characteristic workflows to compare the performance of a commercial cloud with that of a typical HPC system, and it analyzes the various costs associated with running those workflows in the cloud.
Abstract: The proliferation of commercial cloud computing providers has generated significant interest in the scientific computing community. Much recent research has attempted to determine the benefits and drawbacks of cloud computing for scientific applications. Although clouds have many attractive features, such as virtualization, on-demand provisioning, and "pay as you go" usage-based pricing, it is not clear whether they are able to deliver the performance required for scientific applications at a reasonable price. In this paper we examine the performance and cost of clouds from the perspective of scientific workflow applications. We use three characteristic workflows to compare the performance of a commercial cloud with that of a typical HPC system, and we analyze the various costs associated with running those workflows in the cloud. We find that the performance of clouds is not unreasonable given the hardware resources provided, and that performance comparable to HPC systems can be achieved given similar resources. We also find that the cost of running workflows on a commercial cloud can be reduced by storing data in the cloud rather than transferring it from outside.
254 citations
Patent•
IBM1
TL;DR: Workflow systems interact with each other as peers using this mechanism by sending workflow execution requests, workflow script templates, and workflow execution environments to each other as discussed by the authors, where Task Request and Task Response messages are used to standardize the communication between Source Agents and Performer Agents, along with other messages for controlling and queuing Tasks.
Abstract: A mechanism for heterogeneous, peer-to-peer, and disconnected workflow execution across a network infrastructure. Performer Agent entities provide a homogeneous view of humans, applications, and heterogeneous workflow systems and components that act as Performers on the network by executing Tasks. Source Agent entities provide a homogeneous view of heterogeneous service requesters such as workflow scripts executing on different workflow systems, which generate Activities that need to execute on Performers as Tasks. Task Request and Task Response messages are used to standardize the communication between Source Agents and Performer Agents, along with other messages for controlling and queuing Tasks. Workflow systems interact with each other as peers using this mechanism by sending workflow execution requests, workflow script templates, and workflow execution environments to each other. Disconnected operation is handled by ensuring the continuous availability of Source Agents and Performer Agents on the network and providing a mechanism for Sources to disconnect from Source Agents and Performers to disconnect from Performer Agents.
253 citations
11 Sep 2005
TL;DR: A business process model can be adopted directly in the multi-agent system, thus reduce the effort on the validation and verification of the interaction protocol (system specification), and provide a lightweight way of re-design of large component based systems.
Abstract: This paper describes the development of a distributed multi-agent workflow enactment mechanism using the BPEL4WS[1] specification. It demonstrates that a multi-agent protocol (Lightweight Coordination Calculus (LCC)[8]) can be used to interpret a BPEL4WS specification to enable distributed business workflow[5] using web services[2] composition on the multi-agent platform. The key difference between our system and other existing multi-agent based web services composition systems is that with our approach, a business process model(system requirement) can be adopted directly in the multi-agent system, thus reduce the effort on the validation and verification of the interaction protocol (system specification). This approach also provides us with a lightweight way of re-design of large component based systems.
253 citations
TL;DR: A “big data” platform to facilitate the work of geophysicists in interpreting and analyzing large volumes of seismic data with scalable performance on a scalable, distributed computing platform.
Abstract: The modern requirement for analyzing and interpreting ever-larger volumes of seismic data to identify prospective hydrocarbon prospects within stringent time deadlines represents an ongoing challenge in petroleum exploration. To provide a computer-based aid in addressing this challenge, we have developed a “big data” platform to facilitate the work of geophysicists in interpreting and analyzing large volumes of seismic data with scalable performance. We have constructed this platform on a modern distributed-memory infrastructure, providing a customized seismic analytics software development toolkit, and a Web-based graphical workflow interface along with a remote 3D visualization capability. These support the management of seismic data volumes, attributes processing, seismic analytics model development, workflow execution, and 3D volume visualization on a scalable, distributed computing platform. Early experiences show that computationally demanding deep learning methods such as convolutional neural netwo...
253 citations