Impact of data compression on energy consumption of wireless-networked handheld devices
We investigate the use of data compression to reduce the battery consumed by handheld devices when downloading data from proxy servers over a wireless LAN. To make a careful trade-off between the communication energy and the overhead to perform decompression, we experiment with three universal lossless compression schemes, using a popular handheld device in a wireless LAN environment and we find interesting facts. The results show that, from the battery-saving perspective, the gzip compression software (based on LZ77) to be far superior to bzip2 (based on BWT) and compress (based on LZW). We then present an energy model to estimate the energy consumption for the compressed downloading. With this model, we further reduce the energy cost of gzip by interleaving communication with computation and by using a block-by-block selective scheme based on the compression factor of each block. We also use a threshold file size below which the file is not to be compressed before transferring.

title: Compiler algorithms for event variable synchronization
abstract: Event variable synchronization is a well known mecha nism for enforcing data dependences in a program that runs in parallel on a shared memory multiprocessor This paper presents compiler algorithms to automati cally generate event variable synchronization code Pre viously published algorithms dealt with single parallel loops in which dependence distances are constant and known by the compiler However loops in real appli cation programs are often arbitrarily nested Moreover compilers are often unable to determine dependence dis tances In contrast our algorithms generate synchro nization code based directly on array subscripts and do not require constant distances in data dependences The algorithms are designed for arbitrarily nested loops in cluding triangular or trapezoidal loops

title: On Reducing Data Synchronization in Multiprocessed Loops
abstract: In this correspondence we present and prove the correctness of an algorithm for reducing the number of synchronized memory references to shared data elements in multiprocessed loops. Optimizing compilers for shared memory multiprocessors can use this algorithm to reduce synchronization overhead. The algorithm has been implemented as a new module in the multiprocessors version of Parafrase, the restructuring system of the University of Illinois. We present a brief discussion of experiments we performed to asses the effectiveness of this algorithm in reducing the synchronization overhead for the 61 subroutines of EISPACK, a package for computing matrix eigenvectors and eigenvalues.

title: New tiling techniques to improve cache temporal locality
abstract: Tiling is a well-known loop transformation to improve temporal locality of nested loops. Current compiler algorithms for tiling are limited to loops which are perfectly nested or can be transformed, in trivial ways, into a perfect nest. This paper presents a number of program transformations to enable tiling for a class of nontrivial imperfectly-nested loops such that cache locality is improved. We define a program model for such loops and develop compiler algorithms for their tiling. We propose to adopt odd-even variable duplication to break anti- and output dependences without unduly increasing the working-set size, and to adopt speculative execution to enable tiling of loops which may terminate prematurely due to, e.g. convergence tests in iterative algorithms. We have implemented these techniques in a research compiler, Panorama. Initial experiments with several benchmark programs are performed on SGI workstations based on MIPS R5K and R10K processors. Overall, the transformed programs run faster by 9% to 164%.

title: Experience in the Automatic Parallelization of Four Perfect-Benchmark Programs
abstract: This paper discusses the techniques used to hand-parallelize, for the Alliant FX/80, four Fortran programs from the Perfect-Benchmark suite. The paper also includes the execution times of the programs before and after the transformations. The four programs considered here were not effectively parallelized by the automatic translators available to the authors. However, most of the techniques used for hand parallelization, and perhaps all of them, have wide applicability and can be incorporated into existing translators.

title: A theoretical foundation for program transformations to reduce cache thrashing due to true data sharing
abstract: Cache thrashing due to true data sharing can degrade the performance of parallel programs significantly. Our previous work showed that parallel task alignment via program transformations can be quite effective for the reduction of such cache thrashing. In this paper, we present a theoretical foundation for such program transformations. Based on linear algebra and the theory of numbers, our work analyzes the data dependences among the tasks created by a fork-join parallel program and determines at compile time how these tasks should be assigned to processors in order to reduce cache thrashing due to true data sharing. Our analysis and program transformations can be easily performed by compilers for parallel computers.

title: Reducing Energy Consumption of Disk Storage Using Power-Aware Cache Management
abstract: Reducing energy consumption is an important issue for data centers. Among the various components of a data center, storage is one of the biggest consumers of energy. Previous studies have shown that the average idle period for a server disk in a data center is very small compared to the time taken to spin down and spin up. This significantly limits the effectiveness of disk power management schemes. This paper proposes several power-aware storage cache management algorithms that provide more opportunities for the underlying disk power management schemes to save energy. More specifically, we present an off-line power-aware greedy algorithm that is more energy-efficient than Belady’s off-line algorithm (which minimizes cache misses only). We also propose an online power-aware cache replacement algorithm. Our trace-driven simulations show that, compared to LRU, our algorithm saves 16% more disk energy and provides 50% better average response time for OLTP I/O workloads. We have also investigated the effects of four storage cache write policies on disk energy consumption.

title: An Efficient Sort-Based DDM Matching Algorithm for HLA Applications with a Large Spatial Environment
abstract: Simulation is a low cost and safe alternative to solve complex problems in various areas. To promote reuse and interoperability of simulation applications and link geographically dispersed simulation components, distributed simulation was introduced. The high level architecture (HLA) is the IEEE standard for distributed simulation. To optimize communication efficiency between simulation components, HLA defines a data distribution management (DDM) service group for filtering out unnecessary data exchange. It relies on the computation of overlap between update and subscription regions, which is called matching. In this paper, we propose an efficient sort-based DDM matching algorithm for HLA applications with a large spatial environment. A theoretical analysis of our algorithm concludes that it should have good storage and computational scalability. The experimental results have verified the theoretical conclusions by showing that our algorithm has much less storage requirement than the original sort-based matching algorithm and generally has the best computational performance when compared with region-based and the original sort-based matching algorithms.

title: On achieving optimal throughput with network coding
abstract: With the constraints of network topologies and link capacities, achieving the optimal end-to-end throughput in data networks has been known as a fundamental but computationally hard problem. In this paper, we seek efficient solutions to the problem of achieving optimal throughput in data networks, with single or multiple unicast, multicast and broadcast sessions. Although previous approaches lead to solving NP-complete problems, we show the surprising result that, facilitated by the recent advances of network coding, computing the strategies to achieve the optimal end-to-end throughput can be performed in polynomial time. This result holds for one or more communication sessions, as well as in the overlay network model. Supported by empirical studies, we present the surprising observation that in most topologies, applying network coding may not improve the achievable optimal throughput; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.

title: Performance-directed energy management for storage systems
abstract: Energy consumption has become an important issue in the design of battery-operated mobile devices and sophisticated data centers. The storage hierarchy, which includes memory and disks, is a major energy consumer in such systems; especially for high-end servers at data centers. Much work has focused on energy control algorithms for storage systems that transition a device into a low power mode when a certain usage function exceeds a specified threshold. These algorithms are difficult to use in real systems, however, because designers must painstakingly and manually tune threshold values, and even then a performance guarantee is difficult. To address these limitations, we develop three algorithms: 1) a performance guarantee technique that designers can use with any underlying energy-control algorithm 2) a performance-directed control algorithm that periodically assigns a static configuration to different devices by solving an optimization problem 3) another performance-directed control algorithm that dynamically self-tunes according to an optimal set of thresholds

title: Basic Topological Models for Spatial Entities in 3-Dimensional Space
abstract: In recent years, models of spatial relations, especially topological relations, have attracted much attention from the GIS community. In this paper, some basic topologic models for spatial entities in both vector and raster spaces are discussed.It has been suggested that, in vector space, an open set in 1-D space may not be an open set any more in 2-D and 3-D spaces. Similarly, an open set in 2-D vector space may also not be an open set any more in 3-D vector spaces. As a result, fundamental topological concepts such as boundary and interior are not valid any more when a lower dimensional spatial entity is embedded in higher dimensional space. For example, in 2-D, a line has no interior and the line itself (not its two end-points) forms a boundary. Failure to recognize this fundamental topological property will lead to topological paradox. It has also been stated that the topological models for raster entities are different in Z2 and R2. There are different types of possible boundaries depending on the definition of adjacency or connectedness. If connectedness is not carefully defined, topological paradox may also occur. In raster space, the basic topological concept in vector space—connectedness—is implicitly inherited. This is why the topological properties of spatial entities can also be studied in raster space. Study of entities in raster (discrete) space could be a more efficient method than in vector space, as the expression of spatial entities in discrete space is more explicit than that in connected space.