This tutorial serves as a rapid overview of Autodesk’s Maya software. The 3D production pipeline can be broken down into several distinct activities and skill sets - we will cover all of these to give you a sense for building an entire scene from start to finish. The biological topic will be to create a visual depiction of how calcium chelation can affect cadherin flexibility. The tutorial is divided into 5 sections, each of which focus on an aspect of the 3D pipeline:
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Install and run examples Open Grid Services Infrastructure compliant You are a scientist, a businessperson, or an engineer. You are always looking for faster ways to do your computer processing, better ways to store and retrieve your data, more efficient ways to interact with your customers or suppliers or clients, all while spending less money. You may be asking yourself these questions, among others: How can I analyze the value of an investment portfolio in minutes, rather than hours? How can I significantly accelerate the drug discovery process?
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Everything You Wanted to Know about Globus, but Were Afraid To Ask Describing Globus Toolkit Version 4 An Early and Incomplete Draft Please send comments, criticisms, and suggestions to: foster@mcs.anl.gov Preface The Globus Toolkit (GT) has been developed since the late 1990s to support the development of service-oriented distributed computing applications and infrastructures. Core GT components address basic issues relating to security, resource access and management, data movement and management, resource discovery, and so forth. A broader “Globus universe” comprises numerous tools and components that build on core GT4 functionality to provide many useful application- level functions.
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The trend of data intensive grid applications has brought grid storage protocols and servers into focus. The objective of this study is to gain an understanding of how time is spent in the storage protocols and servers. The storage protocols have a variety of tuning parameters. Some parameters improve single client performance at the expense of in- creased server load, thereby limiting the number of served clients. What ultimately matters is the throughput of the whole system. Some param- eters increase the flexibility or security of the system at some expense. The objective of this study is to make such trade-o?s clear and enable easy full system optimization.
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The unbounded increase in the computation and data requirements of scientific applications has necessitated the use of widely distributed compute and storage resources to meet the demand. In a widely distributed environment, data is no more locally accessible and has thus to be remotely retrieved and stored. Efficient and reliable access to data sources and archiving destinations in such an environment brings new challenges. Placing data on temporary local storage devices offers many advantages, but such “data placements” also require careful management of storage resources and data movement, i.e. allocating storage space, staging-in of input data, staging-out of generated data, and de-allocation of local storage after the data is safely stored at the destination. Traditional systems closely couple data placement and computation, and consider data placement as a side effect of computation. Data placement is either embedded in the computation and causes the computation to delay, or performed as simple scripts which do not have the privileges of a job.
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