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Given a transfer function for a differential equation model, an approach for obtaining a solution is by way of bilinear transformation. The bilinear transform approach is a numerical integration scheme which gives a discrete approximation to the differential equation solution. BILIN applies a series of polynomial transformations to the transfer function H(s). As a result, H(s) is mapped into the complex z plane obtaining the discrete transfer function H(z). From H(z), the difference equation is obtained whose solution y(nT) approximates the actual differential solution y(t). Hence, BILIN provides a means for obtaining discrete transfer functions for the design of digital filters and/or solving linear time-invariant differential equations.

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The advent of cluster computing has resulted in a thrust towards providing software mechanisms for reliability on clusters. The prevalent model for such mechanisms is to take a snapshot of the state of an application, called a checkpoint and commit it to stable storage. This checkpoint has sufficient meta-data, so that if the application fails, it can be restarted from the checkpoint. This operation is called a restore. In order to record a process' complete state, both its volatile and persistent state must be checkpointed. Several libraries exist for checkpointing volatile state. Some of these libraries feature incremental checkpointing, where only the changes since the last checkpoint are recorded in the next checkpoint. Such incremental checkpointing is advantageous since otherwise, the time taken for each successive checkpoint becomes larger and larger. Also, when checkpointing is done in increments, we can restore state to any of the previous checkpoints; a vital feature for adaptive applications. This thesis presents a user-level incremental checkpointing library for files: Metamori. This brings the advantages of incremental memory checkpointing to files as well, thereby providing a low-overhead approach to checkpoint persistent state. Thus, the complete state of an application can now be incrementally checkpointed, as compared to earlier approaches where volatile state was checkpointed incrementally but persistent state had no such facilities. / Master of Science

File systems store data in files and organize these files in directories. Over decades, file systems have evolved to handle increasingly large files: they distribute files across a cluster of machines, they parallelize access to these files, they decouple data access from metadata access, and hence they provide scalable file access for high-performance applications. Sadly, most cluster-wide file systems lack any sophisticated support for large directories. In fact, most cluster file systems continue to use directories that were designed for humans, not for large-scale applications. The former use-case typically involves hundreds of files and infrequent concurrent mutations in each directory, while the latter use-case consists of tens of thousands of concurrent threads that simultaneously create large numbers of small files in a single directory at very high speeds. As a result, most cluster file systems exhibit very poor file create rate in a directory either due to limited scalability from using a single centralized directory server or due to reduced concurrency from using a system-wide synchronization mechanism. This dissertation proposes a directory architecture called GIGA+ that enables a directory in a cluster file system to store millions of files and sustain hundreds of thousands of concurrent file creations every second. GIGA+ makes two indexing technique to scale out a growing directory on many servers and an efficient layered design to scale up performance. GIGA+ uses a hash-based, incremental partitioning algorithm that enables highly concurrent directory indexing through asynchrony and eventual consistency of the internal indexing state (while providing strong consistency guarantees to the application data). This dissertation analyzes several trade-offs between data migration overhead, load balancing effectiveness, directory scan performance, and entropy of indexing state made by the GIGA+ design, and compares them with policies used in other systems. GIGA+ also demonstrates a modular implementation that separates directory distribution from directory representation. It layers a client-server middleware, which spreads work among many GIGA+ servers, on top of a backend storage system, which manages on-disk directory representation. This dissertation studies how system behavior is tightly dependent on both the indexing scheme and the on-disk implementations, and evaluates how the system performs for different backend configurations including local and shared-disk stores. The GIGA+ prototype delivers highly scalable directory performance (that exceeds the most demanding Petascale-era requirements), provides the traditional UNIX file system interface (that can run applications without any modifications) and offers a new functionality layered on existing cluster file systems (that lack support for distributed directories)contributions: a concurrent

This paper describes the file format of the climate data container used by the DELPHIN, THERAKLES and NANDRAD simulation programs. The climate data container format holds a binary representation of annual and continuous climatic data needed for hygrothermal transport and building energy simulation models. The content of the C6B-Format is roughly equivalent to the epw-climate data format.

This thesis compares the file organization techniques that are implemented on two different types of computer systems, the large-scale and the small-scale. File organizations from representative computers in each class are examined in detail: the IBM System/370 (OS/370) and the Harris 1600 Distributed Processing System with the Extended Communications Operating System (ECOS). In order to establish the basic framework for comparison, an introduction to file organizations is presented. Additionally, the functional requirements for file organizations are described by their characteristics and user demands. Concluding remarks compare file organization techniques and discuss likely future developments of file systems.