1595687
Does Time-Division Multiplexing Close the Gap between Memory and Optical Communication Speeds?
Optical interconnection networks have the potential of transmitting data much faster than the speed at which this data can be generated at the transmitting nodes or consumed at the receiving nodes. Even when the communication protocols are simplified and most of the protocol signaling at the end nodes is done in hardware, the data cannot be processed at the end nodes at a rate faster than the rate of memory operations. We study the effect of multiplexing the network on both its throughput and latency for different ratios of memory to link transmission speeds. We found that multiplexing reduces the impact of the gap between data transmission and data generation/consumption speeds.
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.
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.
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.
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.
1794602
HDR VolVis: high dynamic range volume visualization
In this paper, we present an interactive high dynamic range volume visualization framework (HDR VolVis) for visualizing volumetric data with both high spatial and intensity resolutions. Volumes with high dynamic range values require high precision computing during the rendering process to preserve data precision. Furthermore, it is desirable to render high resolution volumes with low opacity values to reveal detailed internal structures, which also requires high precision compositing. High precision rendering will result in a high precision intermediate image (also known as high dynamic range image). Simply rounding up pixel values to regular display scales will result in loss of computed details. Our method performs high precision compositing followed by dynamic tone mapping to preserve details on regular display devices. Rendering high precision volume data requires corresponding resolution in the transfer function. To assist the users in designing a high resolution transfer function on a limited resolution display device, we propose a novel transfer function specification interface with nonlinear magnification of the density range and logarithmic scaling of the color/opacity range. By leveraging modern commodity graphics hardware, multiresolution rendering techniques and out-of-core acceleration, our system can effectively produce an interactive visualization of large volume data, such as 2.048/sup 3/.
6386106
Procedural Image Processing for Visualization
We present a novel Procedural Image Processing (PIP) method and demonstrate its applications in visualization. PIP modulates the sampling positions of a conventional image processing kernel (e.g. edge detection filter) through a procedural perturbation function. When properly designed, PIP can produce a variety of styles for edge depiction, varying on width, solidity, and pattern, etc. In addition to producing artistic stylization, in this paper we demonstrate that PIP can be employed to achieve various visualization tasks, such as contour enhancement, focus+context visualization, importance driven visualization and uncertainty visualization. 
 
PIP produces unique effects that often either cannot be easily achieved through conventional filters or would require multiple pass filtering. PIP perturbation functions are either defined by analytical expressions or encoded in pre-generated images. We leverage the programmable fragment shader of the current graphics hardware for achieving the operations in real-time.
124461239
Subband noise estimation for adaptive wavelet shrinkage
In this article, we present an adaptive image denoising method based on subband noise modeling. For wavelet shrinkage, choosing the threshold depends on correctly estimating the noise variance. By modeling the inter-subband noise variance with a parameterized normalized exponential function, the problem becomes identifying the maximum noise variance. Such a maximum exists in the highest decomposition level and can be estimated by locating the extreme of the first derivative of the subband variance function. The experiments demonstrate that our method outperforms peers, especially in the cases of large noise variance.
2000177
A distributed visual surveillance system
We present a distributed vision-based surveillance system. The system acquires and processes grey level images through one or multiple camera units monitoring certain area(s) via a local area network (LAN) and is capable of combining information from multiple camera units to obtain a consensus decision. It can be trained to detect certain type of intrusions, for example pedestrians, a group of pedestrians, vehicles, pets, etc., and minimizes false alerts due to other non-interested intrusions. As a case study, we aim to detect pedestrian/vehicle in an observation area. Our vision-based intrusion detection approach consists of two main steps: background subtraction based hypothesis generation (HG) and appearance-based hypothesis verification (HV). HG hypothesizes possible threats (intrusions), and HV verifies those hypotheses using a Gabor filter for feature extraction and support vector machines (SVMs) for classification. The system has been tested in an unconstrained outdoor environment, illustrating good performance.
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.