6730998
Monitoring remotely executing shared memory programs in software DSMs
Peer-to-peer (P2P) cycle sharing over the Internet has become increasingly popular as a way to share idle cycles. A fundamental problem faced by P2P cycle sharing systems is how to incrementally monitor and verify, with low overhead, the execution of jobs submitted to a remote untrusted hosting machine, or cluster of machines. In this paper, we present the design and implementation of GripCop DSM, a novel incremental execution monitoring and verification scheme for software distributed shared memory (SDSM) programs running on remote clusters. Our scheme maximally leverages the shared memory abstraction provided by the SDSM system by extending the shared memory abstraction to the monitoring process by replicating one of the processes running on the host cluster to verify intermediate results at runtime. Our GripCop DSM employs two monitoring schemes: (i) a full-scale monitoring scheme that completely replicates the computation of a process running on the cluster; and (ii) a decoy monitoring scheme that deceives the host cluster into believing that full-scale monitoring is being performed without it ever actually being done, thereby incurring negligible overhead. Experiments show that the combined use of full-scale and decoy monitoring ensures faithful execution with low performance impact, even over a wide area network
463081
Topology-Aware Routing in Structured Peer-to-Peer Overlay Networks
Structured peer-to-peer (p2p) overlay networks like CAN, Chord, Pastry and Tapestry offer a novel platform for a variety of scalable and decentralized distributed applications. They provide efficient and fault-tolerant routing, object location and load balancing within a self-organizing overlay network. One important aspect of these systems is how they exploit network proximity in the underlying Internet. We present a study of topology-aware routing approaches in p2p overlays, identify proximity neigbor selection as the most promising technique, and present an improved design in Pastry. Results obtained via analysis and via simulation of two large-scale topology models indicate that it is possible to efficiently exploit network proximity in self-organizing p2p substrates. Proximity neighbor selection incurs only a modest additional overhead for organizing and maintaining the overlay network. The resulting locality properties improve application performance and reduce network usage in the Internet substantially. Finally, we show that the impact of proximity neighbor selection on the load balancing in the p2p overlay is minimal.
481550
Improving Fine-Grained Irregular Shared-Memory Benchmarks by Data Reordering
We demonstrate that data reordering can substantially improve the performance of fine-grained irregular shared-memory benchmarks, on both hardware and software shared-memory systems. In particular, we evaluate two distinct data reordering techniques that seek to co-locate in memory objects that are in close proximity in the physical system modeled by the computation. The effects of these techniques are increased spatial locality and reduced false sharing. We evaluate the effectiveness of the data reordering techniques on a set of five irregular applications from SPLASH-2 and Chaos. We implement both techniques in a small library, allowing us to enable them in an application by adding less than 10 lines of code. Our results on one hardware and two software shared-memory systems show that, with data reordering during initialization, the performance of these applications is improved by 12%-99% on the Origin 2000, 30%-366% on TreadMarks, and 14%-269% on HLRC.
1998178
A Hierarchical Approach to Internet Distance Prediction
Internet distance prediction gives pair-wise latency information with limited measurements. Recent studies have revealed that the quality of existing prediction mechanisms from the application perspective is short of satisfactory. In this paper, we explore the root causes and remedies for this problem. Our experience with different landmark selection schemes shows that although selecting nearby landmarks can increase the prediction accuracy for short distances, it can cause the prediction accuracy for longer distances to degrade. Such uneven prediction quality significantly impacts application performance. Instead of trying to select the landmark nodes in some "intelligent" fashion, we propose a hierarchical prediction approach with straightforward landmark selection. Hierarchical prediction utilizes multiple coordinate sets at multiple distance scales, with the "right" scale being chosen for prediction each time. Experiments with Internet measurement datasets show that this hierarchical approach is extremely promising for increasing the accuracy of network distance prediction.
1334946
Program counter based techniques for dynamic power management
Reducing energy consumption has become one of the major challenges in designing future computing systems. We propose a novel idea of using program counters to predict I/O activities in the operating system. We present a complete design of program-counter access predictor (PCAP) that dynamically learns the access patterns of applications and predicts when an I/O device can be shut down to save energy. PCAP uses path-based correlation to observe a particular sequence of program counters leading to each idle period, and predicts future occurrences of that idle period. PCAP differs from previously proposed shutdown predictors in its ability to: (1) correlate I/O operations to particular behavior of the applications and users, (2) carry prediction information across multiple executions of the applications, and (3) attain better energy savings while incurring low mispredictions.
43789567
A Self-Organizing Flock of Condors
13831969
The Communication Performance of the Cray T3D and its Effect on Iterative Solvers
On many distributed memory systems, such as workstation clusters or the Intel iPSC/860, the multigrid algorithm suffers from having extensive communication requirements and, in general, it is not very competitive in comparison to the conjugate gradient algorithm. This is in contrast to the sequential problem whereby the multigrid algorithm is very effective in reducing the global residual, particularly for very large linear systems of equations. These two algorithms are now compared on the Cray T3D for solving very large systems of linear equations (resulted from grids of the order 2563 cells). The communication performance of the Cray T3D is first measured by the standard ping-pong tests and also by practical communication tasks that are found frequently in CFD calculations. It is found that the Cray T3D has a low latency (≈ 6 μs) and a high bandwidth interprocessor communication (120 MB/s) when the low-level intrinsic communication routines are used. As a result, the multigrid algorithm is found to be very competitive when compared with the conjugate gradient algorithm for solving the very large linear systems arising from the Direct Numerical Simulation of turbulent Combustion (DNSC). Results are contrasted by those on the Intel iPSC/860.
22875771
ACO-Steiner: Ant Colony Optimization Based Rectilinear Steiner Minimal Tree Algorithm
The rectilinear Steiner minimal tree (RSMT) problem is one of the fundamental problems in physical design, especially in routing, which is known to be NP-complete. This paper presents an algorithm, called ACO-Steiner, for RSMT construction based on ant colony optimization (ACO). An RSMT is constructed with ants' movements in Hanan grid, and then the constraint of Hanan grid is broken to accelerate ants' movements to improve the performance of the algorithm. This algorithm has been implemented on a Sun workstation with Unix operating system and the results have been compared with the fastest exact RSMT algorithm, GeoSteiner 3.1 and a recent heuristic using batched greedy triple construction (BGTC). Experimental results show that ACO-Steiner can get a short running time and keep the high performance. Furthermore, it is also found that the ACO-Steiner can be easily extended to be used to some other problems, such as rectilinear Steiner minimal tree avoiding obstacles, and congestion reduction in global routing.
834526
Efficient 3D reconstruction for face recognition
Face recognition with variant pose, illumination and expression (PIE) is a challenging problem. In this paper, we propose an analysis-by-synthesis framework for face recognition with variant PIE. First, an efficient two-dimensional (2D)-to-three-dimensional (3D) integrated face reconstruction approach is introduced to reconstruct a personalized 3D face model from a single frontal face image with neutral expression and normal illumination. Then, realistic virtual faces with different PIE are synthesized based on the personalized 3D face to characterize the face subspace. Finally, face recognition is conducted based on these representative virtual faces. Compared with other related work, this framework has following advantages: (1) only one single frontal face is required for face recognition, which avoids the burdensome enrollment work; (2) the synthesized face samples provide the capability to conduct recognition under difficult conditions like complex PIE; and (3) compared with other 3D reconstruction approaches, our proposed 2D-to-3D integrated face reconstruction approach is fully automatic and more efficient. The extensive experimental results show that the synthesized virtual faces significantly improve the accuracy of face recognition with changing PIE.
16350167
Efficient propagation for face annotation in family albums
In this paper, we propose and investigate a new user scenario for face annotation, in which users are allowed to multi-select a group of otogras and assign names to these otogras. The system will then attempt to propagate names from otogra level to face level, i.e. to infer the correspondence between name and face. Given the face similarity measure which combines methodologies from face recognition and content-based image retrieval, we formulate name propagation as an optimization problem. We define the objective function as the sum of similarities between each pair of faces of the same individual in different otogras, and propose an iterative optimization algorithm to infer the optimal correspondence. To make the propagation result reliable, a reject scheme is adopted to reject those with low confidence scores. Furthermore, we investigate the combination and alternation of browsing mode for propagation and viewer mode for annotation, so that each mode can benefit from additional inputs from the other mode. The experimental evaluation has been conducted within a typical family album of over one thousand otogras and the results show that the proposed approach is effective and efficient in automated face annotation in family albums.
15964904
JPEG2000 Image Adaptation for MPEG-21 Digital Items
MPEG-21 user cases bring out a scenario of Universal Multimedia Access which is becoming the reality: people use different devices such as desktop PC, personal digital assistant as well as smartphone to access multimedia information. Viewing images on mobile devices is more and more popular than before. However, due to the screen size limitation, the experience of viewing large image on small screen devices is awkward. In this paper, an enhanced JPEG2000 image adaptation system is proposed for MPEG-21 digital item adaptation. The image is adapted considering both visual attentive region(s) of image and terminal screen size. Through the subjective testing, the system has been approved to be a solution of efficiently displaying large images in different devices.