14827113
An empirical approach for efficient all-to-all personalized communication on Ethernet switched clusters
All-to-all personalized communication (AAPC) is one of the most commonly used communication patterns in parallel applications. Developing an efficient AAPC routine is difficult since many system parameters can affect the performance of an AAPC algorithm. In this paper, we investigate an empirical approach for automatically generating efficient AAPC routines for Ethernet switched clusters. This approach applies when the application execution environment is decided, and it allows efficient customized AAPC routines to be created. Experimental results show that the empirical approach generates routines that consistently achieve high performance on clusters with different network topologies. In many cases, the automatically generated routines out-perform conventional AAPC implementations to a large degree.
7026270
Branch elimination by condition merging
Conditional branches are expensive. Branches require a significant percentage of execution cycles since they occur frequently and cause pipeline flushes when mispredicted. In addition, branches result in forks in the control flow, which can prevent other code-improving transformations from being applied. In this paper we describe profile-based techniques for replacing the execution of a set of two or more branches with a single branch on a conventional scalar processor. These sets of branches can include tests of multiple variables. For instance, the test if (p1 ! = 0 && p2 ! = 0), which is testing for NULL pointers, can be replaced with if (p1 & p2 ! = 0). Program profiling is performed to target condition merging along frequently executed paths. The results show that eliminating branches by merging conditions can significantly reduce the number of conditional branches executed in non-numerical applications.
18020602
Automatic validation of code-improving transformations on low-level program representations
This paper presents a general approach for automatically validating code-improving transformations on low-level program representations. The approach ensures the correctness of compiler and hand-specified optimizations at the machine instruction level. The method verifies the semantic equivalence of the program representation before and after a transformation to determine the validity of the transformation. To verify that the transformation is semantics preserving, the method derives semantic effects from the instructions that span the execution paths affected by the transformation. The semantics are preserved if the normalized semantic effects are unchanged. A validating compilation system was implemented that is able to validate traditional compiler transformations and more powerful transformations that modify the branch structure of a program.
8426908
Branch Elimination via Multi-variable Condition Merging
Conditional branches are expensive. Branches require a significant percentage of execution cycles since they occur frequently and cause pipeline flushes when mispredicted. In addition, branches result in forks in the control flow, which can prevent other code-improving transformations from being applied. In this paper we describe profile-based techniques for replacing the execution of a set of two or more branches with a single branch on a conventional scalar processor. First, we gather profile information to detect the frequently executed paths in a program. Second, we detect sets of conditions in frequently executed paths that can be merged into a single condition. Third, we estimate the benefit of merging each set of conditions. Finally, we restructure the control flow to merge the sets that are deemed beneficial. The results show that eliminating branches by merging conditions can significantly reduce the number of conditional branches performed in non-numerical applications.
33385860
An empirical study of reliable multicast protocols over Ethernet-connected networks
Recent advances in multicasting over the Internet present new opportunities for improving communication performance for clusters of workstations. Realizing collective communication over reliable multicast can achieve higher performance than over reliable unicast primitives. The standard IP multicast, however, only supports unreliable multicast, which is difficult to use for building high level message passing routines. Thus, reliable multicast primitives must be implemented over the standard IP multicast to facilitate the use of multicast for high-performance communication on clusters of workstations. Although many reliable multicast protocols have been proposed for the wide area Internet environment, the impact of special features of local area networks (LANs) on the performance of the reliable multicast protocols has not been thoroughly studied. Efficient reliable multicast protocols for LANs must exploit these features to achieve the best performance. In this paper, we present our implementation of four types of reliable multicast protocols: the ACK-based protocols, the NAK-based protocols with polling, the ring-based protocols and the tree-based protocols. The protocols are implemented over IP multicast using the standard UDP interface. We evaluate the performance of the protocols over Ethernet-connected networks, study the impact of some special features of the Ethernet on the performance of the protocols and investigate the methods to exploit these features to improve communication performance.
3570050
Algorithms for Supporting Compiled Communication
We investigate the compiler algorithms to support compiled communication in multiprocessor environments and study the benefits of compiled communication, assuming that the underlying network is an all-optical time-division-multiplexing (TDM) network. We present an experimental compiler, E-SUIF, that supports compiled communication for High Performance Fortran (HPF) like programs on all-optical TDM networks, and describe and evaluate the compiler algorithms used in E-SUIF. We further demonstrate the effectiveness of compiled communication on all-optical TDM networks by comparing the performance of compiled communication with that of a traditional communication method using a number of application programs.
223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed method.
27055322
A Fast Evolution Strategies Based Approach To Image Registration
An image registration approach based on Evolution Strategies is proposed. In image registration, an invariant reference needs to be established within each source image, which is unavailable in many cases. To solve this problem, feature configuration (which is defined as the cluster of feature vectors on an image representing homogeneous feature distribution,) is employed to describe the object inside the scene. Instead of finding the correspondence of the entire image, the spatial relationships of the feature configuration in every source image are discovered with Evolution Strategies (ES). While one approach, even this one, may not be suitable for every image domain, the ES approach has many advantages. Compared to some methods, it is computationally effective; compared to other, it is capable of discovering transformations of larger scope (e.g., greater rotation angles or translation distances etc.) The search structure we use is an ellipsoid. The results from various images prove it to be an efficient and effective method.
10910603
Hybrid Forward Resampling and Volume Rendering
The transforming and rendering of discrete objects, such as traditional images (with or without depths) and volumes, can be considered as resampling problem – objects are reconstructed, transformed, filtered, and finally sampled on the screen grids. In resampling practices, discrete samples (pixels, voxels) can be considered either as infinitesimal sample points (simply called points) or samples of a certain size (splats). Resampling can also be done either forwards or backwards in either the source domain or the target domain. In this paper, we present a framework that features hybrid forward resampling for discrete rendering. Specifically, we apply this framework to enhance volumetric splatting. In this approach, minified voxels are taken simply as points filtered in screen space; while magnified voxels are taken as spherical splats. In addition, we develop two techniques for performing accurate and efficient perspective splatting. The first one is to efficiently compute the 2D elliptical geometry of perspectively projected splats; the second one is to achieve accurate perspective reconstruction filter. The results of our experiments demonstrate both the effectiveness of antialiasing and the efficiency of rendering using this
8920686
Population Sizing Based on Landscape Feature
Population size for EvolutionaryAlgorithms is usually an empirical parameter. We study the population size from aspects of fitness landscapes' ruggedness and Probably Approximately Correct (PAC) learning theory.
6706494
Real-Time Sensor Fusion Framework for Distributed Intelligent Sensors
Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor fusion framework (RTSFF) based on distributed intelligent sensor network. The RTSFF is an open architecture which consists of four layers – the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The transducer layer is populated with intelligent sensors. The learning ability of the intelligent sensor model enables it to extract characteristics of monitored signal. The representation issue is managed at this level. After describing the RTSFF, the paper then focuses on the fundamental units of the framework, the highly autonomous transducers.