OBFS: A File System for Object-Based Storage Devices
The object-based storage model, in which files are made up of o ne or more data objects stored on self-contained Object-Based Storage Devices (OSDs), is em erging as an architecture for distributed storage systems. The workload presented to the OSDs will be q uite different from that of generalpurpose file systems, yet many distributed file systems employ general-purpose file systems as their underlying file system. We present OBFS, a small and highly ef ficient file system designed for use in OSDs. Our experiments show that our user-level implement ation of OBFS outperforms Linux Ext2 and Ext3 by a factor of two or three, and while OBFS is 1/25 the size of XFS, it provides only slightly lower read performance and 10%‐40% higher write pe rformance.

title: Using MEMS-based storage to boost disk performance
abstract: Non-volatile storage technologies such as flash memory, magnetic RAM (MRAM), and MEMS-based storage are emerging as serious alternatives to disk drives. Among these, MEMS storage is predicted to be the least expensive and highest density, and at about 1 ms access times still considerably faster than hard disk drives. Like the other emerging non-volatile storage technologies, it is highly suitable for small mobile devices but it is expensive to replace hard drives entirely. Its non-volatility, dense storage, and high performance still make it an ideal candidate for the secondary storage subsystem. We examine the use of MEMS storage in the storage hierarchy and show that using a technique called MEMS caching disk, we can achieve 30-49% of the pure MEMS storage performance by using only a small amount (3% of the disk capacity) of MEMS storage in conjunction with a standard hard drive. The resulting system is ideally suited for commercial packaging with a small MEMS device included as part of a standard disk controller or paired with a disk.

title: Embedded Multi-Processor System-on-chip (MPSoC) design considering process variations
abstract: As technology scales, the delay uncertainty caused by process variations has become increasingly pronounced in deep sub-micron designs. As a result, a paradigm shift from deterministic to statistical design methodology at all levels of the design hierarchy is inevitable (Borkar, 2005). As part of two NSF projects (NSF CNS CAREER 0643902 and NSF CNS 0720659), a variation-aware task allocation and scheduling method for multiprocessor system-on-chip (MPSoC) architectures is proposed, to mitigate the impact of parameter variations. A new design metric, called performance yield and defined as the probability of the assigned schedule meeting the predefined performance constraints, is used to guide the task allocation and scheduling procedure. An efficient yield computation method for task scheduling complements and significantly improves the effectiveness of the proposed variation-aware scheduling algorithm. Experimental results show that our variation-aware scheduler achieves significant yield improvements.

title: Connected Dominating Sets in Wireless Networks with Different Transmission Ranges
abstract: Since there is no fixed infrastructure or centralized management in wireless ad hoc networks, a Connected Dominating Set (CDS) has been proposed to serve as a virtual backbone. The CDS of a graph representing a network has a significant impact on the efficient design of routing protocols in wireless networks. This problem has been studied extensively in Unit Disk Graphs (UDG), in which all nodes have the same transmission ranges. However, in practice, the transmission ranges of all nodes are not necessarily equal. In this paper, we model a network as a disk graph and introduce the CDS problem in disk graphs. We present two efficient approximation algorithms to obtain a minimum CDS. The performance ratio of these algorithms is constant if the ratio of the maximum transmission range over the minimum transmission range in the network is bounded. These algorithms can be implemented as distributed algorithms. Furthermore, we show a size relationship between a maximal independent set and a CDS as well as a bound of the maximum number of independent neighbors of a node in disk graphs. The theoretical analysis and simulation results are also presented to verify our approaches.

title: Process-Variation-Aware Adaptive Cache Architecture and Management
abstract: Fabricating circuits that employ ever-smaller transistors leads to dramatic variations in critical process parameters. This in turn results in large variations in execution/access latencies of different hardware components. This situation is even more severe for memory components due to minimum-sized transistors used in their design. Current design methodologies that are tuned for the worst case scenarios are becoming increasingly pessimistic from the performance angle, and thus, may not be a viable option at all for future designs. This paper makes two contributions targeting on-chip data caches. First, it presents an adaptive cache management policy based on nonuniform cache access. Second, it proposes a latency compensation approach that employs several circuit-level techniques to change the access latency of select cache lines based on the criticalities of the load instructions that access them. Our experiments reveal that both these techniques can recover significant amount of the lost performance due to worst case designs.

title: Connected Dominating Set

title: Variation-aware resource sharing and binding in behavioral synthesis
abstract: As technology scales, the delay uncertainty caused by process variations has become increasingly pronounced in deep submicron designs. In the presence of process variations, worst-case timing analysis may lead to overly conservative synthesis, and may end up using excess resources to guarantee design constraints. In this paper, we propose an efficient variation-aware resource sharing and binding algorithm in behavioral synthesis, which takes into account the performance variations for functional units. The performance yield, which is defined as the probability that the synthesized hardware meets the target performance constraints, is used to evaluate the synthesis result. An efficient metric called statistical performance improvement, is used to guide resource sharing and binding. The proposed algorithm is evaluated within a commercial synthesis framework that generates optimized RTL netlists from behavioral specifications. The effectiveness of the proposed algorithm is demonstrated with a set of industrial benchmark designs, which consist of blocks that are commonly used in wireless and image processing applications. The experimental results show that our method achieves an average 33% area reduction over traditional methods, which are based on the worst-case delay analysis, with an average 10% run time overhead.