Choosing between remote I/O versus staging in distributed environments

Today, scientifi_x000C_c applications and experiments have become increasingly complex and more demanding in terms of their computational and data requirements. The amount of data generated and used has grown at a very rapid rate. As tens or hundreds of terabytes of data for a single application is very common today; petabytes and even exabytes of data will be very common in a few years. One of the major challenges in distributed computing environments is how to access these large datasets remotely over the network. Data staging and remote I/O are the most widely used data access methods for distributed applications. Application developers generally chose one over the other intuitively without making any scienti_x000C_fic comparison specifi_x000C_c to their applications since there is no generic model available that they can use. In this thesis, we develop generic models and set guidelines for the application developers which would help them to choose the most appropriate data access method for their application. We de_x000C_fine the parameters that potentially aff_x000B_ect the end-to-end performance of the distributed applications which need to access remote data. To achieve our goal, we implement a series of synthetic benchmark applications to simulate di_x000B_fferent data access patterns. We run these benchmark applications on diff_x000B_erent distributed computing settings with di_x000B_fferent parameters, such as network bandwidth, server and client capabilities, and data access ratio. We also use di_x000B_fferent remote I/O protocols to show the importance of the protocol in making a decision. We use regression analysis to develop applicable generic models for comparing diff_x000B_erent data access methods, and test our models in a real life application. The main contribution of our thesis is generic models that can be applied to most data-intensive distributed applications to decide the best data access technique for those applications. Our models provide the scientists and application developers an opportunity to choose the best data access method before actually running the application

A MIDDLE-WARE LEVEL CLIENT CACHE FOR A HIGH PERFORMANCE COMPUTING I/O SIMULATOR

This thesis describes the design and run time analysis of the system level middle-ware cache for Hecios. Hecios is a high performance cluster I/O simulator. With Hecios, we provide a simulation environment that accurately captures the performance characteristics of all the components in a clusterwide parallel file system. Hecios was specifically modeled after PVFS2. It was designed to be extensible and to easily allow for various component modules to be easily replaced by those that model other system types. Built around the OMNeT++ simulation package, Hecios\u27 inner-cluster communication module is easily adaptable to any TCP/IP based protocol and all standard network interface cards, switches, hubs, and routers. We will examine the system cache component and describe a methodology for implementing other coherence and replacement techniques within Hecios. Similar to other cache simulation tools, we allow the size of the system cache to be varied independently of the replacement policy and caching technique used

Data Access in Wide Area Networks of Heterogeneous Workstations

The accessibility of data in wide area networks can be difficult. This research shows the use of the Internet Backplane Protocol (IBP) along with a modified version of the C standard I/O library that can allow data to be easily accessible without having to make major modifications to legacy code. In fact if legacy programs only use standard input and output routines, they need only be recompiled to effect a homogeneous file system. It also demonstrates that this access is predictable enough to make decisions on what data to access and in what fashion that access is most effective

Remote I/O : fast access to distant storage.

As high-speed networks make it easier to use distributed resources, it becomes increasingly common that applications and their data are not colocated. Users have traditionally addressed this problem by manually staging data to and from remote computers. We argue instead for a new remote I/O paradigm in which programs use familiar parallel I/O interfaces to access remote file systems. In addition to simplifying remote execution, remote I/O can improve performance relative to staging by overlapping computation and data transfer or by reducing communication requirements. However, remote I/O also introduces new technical challenges in the areas of portability, performance, and integration with distributed computing systems. We propose techniques designed to address these challenges and describe a remote I/O library called RIO that we have developed to evaluate the effectiveness of these techniques. RIO addresses issues of portability by adopting the quasi-standard MPI-IO interface and by defining a RIO device and RIO server within the ADIO abstract I/O device architecture. It addresses performance issues by providing traditional I/O optimizations such as asynchronous operations and through implementation techniques such as buffering and message forwarding to off load communication overheads. RIO uses the Nexus communication library to obtain access to configuration and security mechanisms provided by the Globus wide area computing tool kit. Microbenchmarks and application experiments demonstrate that our techniques achieve acceptable performance in most situations and can improve turnaround time relative to staging

Remote I/O: Fast Access to Distant Storage

As high-speed networks make it easier to use distributed resources, it becomes increasingly common that applications and their data are not colocated. Users have traditionally addressed this problem by manually staging data to and from remote computers. We argue instead for a new remote I/O paradigm in which programs use familiar parallel I/O interfaces to access remote filesystems. In addition to simplifying remote execution, remote I/O can improve performance relative to staging by overlapping computation and data transfer or by reducing communication requirements. However, remote I/O also introduces new technical challenges in the areas of portability, performance, and integration with distributed computing systems. We propose techniques designed to address these challenges and describe a remote I/O library called RIO that we have developed to evaluate the effectiveness of these techniques. RIO addresses issues of portability by adopting the quasi-standard MPI-IO interface and by de..