Computational Grids1. Introduction2. Evolution2.1. Clustering2.2. Heterogeneous distributed computing2.3. Metacomputing3. Grid Characteristics3.1. Scaling and selection3.2. Heterogeneity3.3. Unpredictable structure3.4. Dynamic and unpredictable behavior3.5. Multiple administrative domains4. Applications4.1. Distributed supercomputing4.2. High-throughput4.3. On-demand4.4. Collaborative4.5. Data-intensive5. The Globus Metacomputing Toolkit5.1. Resource location and allocation5.2. Communications5.3. Resource information service5.4. Authentication interface5.5. Executable management5.6. Remote data access5.7. Health and status6. Summary7. ReferencesAaron WittEECC 756May 17, 1999Computational Grids1. IntroductionAdvancements in networking have for the first time allowed levels of communication, and therefore cooperation, that were previously unattainable. As the next logical step in high performance distributed computing, computational grids seek to attain levels of performance never seen before by connecting computers from around the world together into a single machine capable of executing a wide array of parallel applications. Such a system, providing such great levels of performance, enables classifications of applications that were also previously unrealistic.However, this type of distributed system really defines a whole new model for computing. Instead of an application being restricted by the computing power of the local system, the production of computational power is now de-coupled from the its use. This concept introduces new avenues for programming models as well, as the focus of a grid application is now on locating the appropriate resourcesto run the application and describing in a general way the operation of the algorithm, rather than specifying a low level sequence of processor commands that is not easily portable to other architectures.Attaining this goal requires meeting a number of significant challenges, however. Foremost, a computational grid will be an inherently dynamic system, as nodes and entire sites are brought on and offline. Changes in network loading and demand which affect the system performance will increase the dynamic aspect of the environment. Secondly, the heterogeneous nature of the resources in the grid must not only be supported, but exploited in order to achieve the best possible performance.In this paper we will develop a set of characteristics that better define a computation grid, examine some of the application areas that are enabled through grid technologies and provide an overview of the Globus Metacomputing Toolkit which attempts to provide a standard interface through which grid components can be build.2. EvolutionThe construction of computational grids is directly based off the techniques used in earlier distributed systems. These systems simply placed more stringent requirements on the type of computational resources used in the system and the scale to which they can be distributed.2.1. ClusteringThe term clustering is usually used to refer to a collection of homogeneous workstations connected together on a local area network and used as a single parallel computer. Typically, these workstations are off the shelf PCs using standard Ethernet/IP interconnections. This type of environment is inexpensive to set up, and the wide availability of message passing libraries like PVM have made clusters the most numerous type of parallel computers to date. This environment is exactly what is currently in existence at RIT.However, there have been several different projects to create higher performance clusters than the simple version described above. Often, this involves enhancements to two specific components of the system.The first of these is the physical interconnection system. Ethernet is a relatively slow connection and cannot provide the network performance needed for high performance distributed computing. Although switched megabit and gigabit ethernet networks improve upon their predecessor, the highest performance clusters use special purpose interconnection hardware like that provided by Myrinet, Servernet or VIA.The second enhancement is in the form of special purpose communication protocols. Standard TCP/IP communication requires too much overhead to achieve the desired performance. One such solution is the FastMessages package that is part of the High Performance Virtual Machine software used in the NCSA NTsupercluster. This messaging protocol is optimized for the low-latency, high-bandwidth environment needed for optimal performance in favor of some of the error recovery options available with standard TCP/IP. Using both the Myrinet interconnection hardware and HPVM, the NCSA NT supercluster has been able to achieve processing rates of over 4 gigaflops.NT Supercluster Network Topology2.2. Heterogeneous distributed computingThe next obvious step from localized groups of homogenous machines is to localized groups of heterogeneous machines. The focus of these machines was interoperability, both amongst differing hardware platforms and differing operating systems. Typically, they used existing, widely used application interfaces like RPC to achieve this interoperability.While there are working implementations of this class of machine, they have in general not achieved much of the potential performance available. This in part due to the fact that while these machines allowed heterogeneity, they did not exploit it.2.3. MetacomputingThe final leap is to create distributed groups of heterogeneous machines, or in essence, making unlike supercomputers talk to each other and inter-operate. The goal in this type of machine is to exploit the characteristics of each machine rather than to abstract them. For example, if an application contained somevector code, this portion of the code would be executed on a vector machine in the metacomputer, while themassively parallel code would be executed on a massively parallel machine or cluster.Here our focus is on both interoperability and performance. We already know how to create high performance SMPs and supercomputers. Existing fiber interconnection technologies can be used to bridge the gap between supercomputer sites and still maintain the performance level needed. All that is then required to create a metacomputer, or computational grid, are the software components to provide the interoperability and other needed services.3. Grid CharacteristicsNow that we have described