GPUs as Storage System Accelerators

Massively multicore processors, such as Graphics Processing Units (GPUs), provide, at a comparable price, a one order of magnitude higher peak performance than traditional CPUs. This drop in the cost of computation, as any order-of-magnitude drop in the cost per unit of performance for a class of system components, triggers the opportunity to redesign systems and to explore new ways to engineer them to recalibrate the cost-to-performance relation. This project explores the feasibility of harnessing GPUs' computational power to improve the performance, reliability, or security of distributed storage systems. In this context, we present the design of a storage system prototype that uses GPU offloading to accelerate a number of computationally intensive primitives based on hashing, and introduce techniques to efficiently leverage the processing power of GPUs. We evaluate the performance of this prototype under two configurations: as a content addressable storage system that facilitates online similarity detection between successive versions of the same file and as a traditional system that uses hashing to preserve data integrity. Further, we evaluate the impact of offloading to the GPU on competing applications' performance. Our results show that this technique can bring tangible performance gains without negatively impacting the performance of concurrently running applications.Comment: IEEE Transactions on Parallel and Distributed Systems, 201

Consumer Adoption of Self-Service Technologies in the Context of the Jordanian Banking Industry: Examining the Moderating Role of Channel Types

YesThis study aimed to examine the key factors predicting Jordanian consumers’ intentions and usage of three types of self-service banking technologies. This study also sought to test if the impacts of these main predictors could be moderated by channel type. This study proposed a conceptual model by integrating factors from the unified theory of acceptance and use of technology (UTAUT), along with perceived risk. The required data were collected from a convenience sample of Jordanian banking customers using a survey questionnaire. The statistical results strongly support the significant influence of performance expectancy, social influence, and perceived risk on customer intentions for the three types of SSTs examined. The results of the X2 differences test also indicate that there are significant differences in the influence of the main predictors due to the moderating effect of channel type. One of the key contributions of this study is that three types of SSTs were tested in a single study, which had not been done before, leading to the identification of the factors common to all three types, as well as the salient factors unique to each type

Accelerating irregular applications on parallel hybrid platforms

Future high-performance computing systems will be hybrid; they will include processors optimized for sequential processing and massively-parallel accelerators. Platforms based on Graphics Processing Units (GPUs) are an example of this hybrid architecture, they integrate commodity CPUs and GPUs. This architecture promises intriguing opportunities: within the same dollar or energy budget, GPUs offer a significant increase in peak processing power and memory bandwidth compared to traditional CPUs, and are, at the same time, generally-programmable. The adoption of GPU-based platforms, however, faces a number of challenges, including the characterization of time/space/power tradeoffs, the development of new algorithms that efficiently harness the platform and abstracting the accelerators in a generic yet efficient way to simplify the task of developing applications on such hybrid platforms. This dissertation explores solutions to the abovementioned challenges in the context of an important class of applications, namely irregular applications. Compared to regular applications, irregular applications have unpredictable memory access patterns and typically use reference-based data structures, such as trees or graphs; moreover, new applications in this class operate on massive datasets. Using novel workload partitioning techniques and by employing data structures that better match the hybrid platform characteristics, this work demonstrates that significant performance gains, in terms of both time to solution and energy, can be obtained when partitioning the irregular workload to be processed concurrently on the CPU and the GPU.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

Exploring data reliability tradeoffs in replicated storage systems

This thesis explores the feasibility of a cost-efficient storage architecture that offers the reliability and access performance characteristics of a high-end system. This architecture exploits two opportunities: First, scavenging idle storage from LAN-connected desktops not only offers a low-cost storage space, but also high I/O throughput by aggregating the I/O channels of the participating nodes. Second, the two components of data reliability – durability and availability – can be decoupled to control overall system cost. To capitalize on these opportunities, we integrate two types of components: volatile, scavenged storage and dedicated, yet low-bandwidth durable storage. On the one hand, the durable storage forms a low-cost back-end that enables the system to restore the data the volatile nodes may lose. On the other hand, the volatile nodes provide a high-throughput front-end. While integrating these components has the potential to offer a unique combination of high throughput, low cost, and durability, a number of concerns need to be addressed to architect and correctly provision the system. To this end, we develop analytical- and simulation-based tools to evaluate the impact of system characteristics (e.g., bandwidth limitations on the durable and the volatile nodes) and design choices (e.g., replica placement scheme) on data availability and the associated system costs (e.g., maintenance traffic). Further, we implement and evaluate a prototype of the proposed architecture: a GridFTP server that aggregates volatile resources. Our evaluation demonstrates an impressive, up to 800MBps transfer throughput for the new GridFTP service.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat

Configurable Security for Scavenged Storage Systems

Scavenged storage systems harness unused disk space from individual workstations the same way idle CPU cycles are harnessed by desktop grid applications lik