Xiaobai Sun

Video rate spectral imaging using a coded aperture snapshot spectral imager.

We have previously reported on coded aperture snapshot spectral imagers (CASSI) that can capture a full frame spectral image in a snapshot. Here we describe the use of CASSI for spectral imaging of a dynamic scene at video rate. We describe significant advances in the design of the optical system, system calibration procedures and reconstruction method. The new optical system uses a double Amici prism to achieve an in-line, direct view configuration, resulting in a substantial improvement in image quality. We describe NeAREst, an algorithm for estimating the instantaneous three-dimensional spatio-spectral data cube from CASSIs two-dimensional array of encoded and compressed measurements. We utilize CASSIs snapshot ability to demonstrate a spectral image video of multi-colored candles with live flames captured at 30 frames per second.

A workload-based analysis of software aging, and rejuvenation

We present a hierarchical model for the analysis of proactive fault management in the presence of system resource leaks. At the low level of the model hierarchy is a degradation model in which we use a nonhomogeneous Markov chain to establish an explicit connection between resource leaks, and the failure rate. With the degradation model, we prove that the failure rate is asymptotically constant in the absence of resource leaks, and it is increasing as leaks occur & accumulate, which confirms the resource leaks as an aging source. The proactive fault management (PFM) is modeled at the higher level as a semi-Markov process. The PFM model takes as input the degradation analysis from the low-level model, and allows us to determine optimal rejuvenation schedules with respect to various system measures.

Algorithm 807: The SBR Toolbox—software for successive band reduction

We present a software toolbox for symmetric band reduction via orthogonal transformations, together with a testing and timing program. The toolbox contains drivers and computational routines for the reduction of full symmetric matrices to banded form and the reduction of banded matrices to narrower banded or tridiagonal form, with optional accumulation of the orthogonal transformations, as well as repacking routines for storage rearrangement. The functionality and the calling sequences of the routines are described, with a detailed discussion of the “control” parameters that allow adaptation of the codes to particular machine and matrix characteristics. We also briefly describe the testing and timing program included in the toolbox.

A framework for symmetric band reduction

We develop an algorithmic framework for reducing the bandwidth of symmetric matrices via orthogonal similarity transformations. This framework includes the reduction of full matrices to banded or tridiagonal form and the reduction of banded matrices to narrower banded or tridiagonal form, possibly in multiple steps. Our framework leads to algorithms that require fewer floating-point operations than do standard algorithms, if only the eigenvalues are required. In addition, it allows for space-time tradeoffs and enables or increases the use of blocked transformations.

HDR Deghosting: How to Deal with Saturation?

We present a novel method for aligning images in an HDR (high-dynamic-range) image stack to produce a new exposure stack where all the images are aligned and appear as if they were taken simultaneously, even in the case of highly dynamic scenes. Our method produces plausible results even where the image used as a reference is either too dark or bright to allow for an accurate registration.

A Note On Parallel Matrix Inversion

We present one-sweep parallel algorithms for the inversion of general and symmetric positive definite matrices. The algorithms feature simple programming and performance optimization while maintaining the same arithmetic cost and numerical properties of conventional inversion algorithms. Our experiments on a Cray T3E-600 and a Beowulf cluster demonstrate high performance of implementations for distributed memory parallel computers.

A BLAS-3 Version of the QR Factorization with Column Pivoting

The QR factorization with column pivoting (QRP), originally suggested by Golub [Numer. Math., 7 (1965), 206--216], is a popular approach to computing rank-revealing factorizations. Using Level 1 BLAS, it was implemented in LINPACK, and, using Level 2 BLAS, in LAPACK. While the Level 2 BLAS version delivers superior performance in general, it may result in worse performance for large matrix sizes due to cache effects. We introduce a modification of the QRP algorithm which allows the use of Level 3 BLAS kernels while maintaining the numerical behavior of the LINPACK and LAPACK implementations. Experimental comparisons of this approach with the LINPACK and LAPACK implementations on IBM RS/6000, SGI R8000, and DEC AXP platforms show considerable performance improvements.

A Matrix Version of the Fast Multipole Method

We present a matrix interpretation of the three-dimensional fast multipole method (FMM). The FMM is for efficient computation of gravitational/electrostatic potentials and fields. It has found various applications and inspired the design of many efficient algorithms. The one-dimensional FMM is well interpreted in terms of matrix computations. The three-dimensional matrix version reveals the underlying matrix structures and computational techniques used in FMM. It also provides a unified view of algorithm variants as well as existing and emerging implementations of the FMM.

Adaptive software rejuvenation: degradation model and rejuvenation scheme

We present a framework of adaptive estimation and rejuvenation of software system performance in the presence of aging sources. The framework specifies that a degradation model not only describe an aging process but also enable the adaptation of model-based performance estimates to on-line measurements of data pertaining to the aging process. The adaptive estimation uses model-based a priori estimation and obtains a posteriori estimation based on the data measurements. With the adaptive estimation, the rejuvenation policy determines the time epochs for data collection and rejuvenation according to system dynamics. In the specific context of resource leaks previously assumed to lead to aging, we present a non-homogeneous Markov model to explicitly establish a connection between resource leaks and the failure rate. We demonstrate an increasing failure rate in the presence of resource leaks. 1. Introduction: the Adaptation Problem We present a framework for adaptive estimation and rejuvenation of software system performance in the presence of aging sources. We are concerned with system resource loss, in particular, memory leakage. Memory is indispensable in computer and communication systems. Memory leakage is a typical aging source for server systems due to software bugs in the client applications that use server resources. Our framework for adaptive estimation and rejuvenation consists of three integral components: a degradation model, an adaptive estimation scheme, and an adaptive rejuvenation scheduling policy. The degradation model allows adaptation of model-based performance estimates to on-line measurements of data pertaining to the aging process. The adaptive estimation scheme uses the model-based a priori estimation and obtains a posteriori estimation based on the measurements. With the adaptive estimation, the rejuvenation scheduling policy determines time epochs for data

Parallel search of k-nearest neighbors with synchronous operations

We present a new study of parallel algorithms for locating k-nearest neighbors (kNN) of each single query in a high dimensional (feature) space on a many-core processor or accelerator that favors synchronous operations, such as on a graphics processing unit. Exploiting the intimate relationships between two primitive operations, select and sort, we introduce a cohort of truncated sort algorithms for parallel kNN search. The truncated bitonic sort (TBiS) in particular has desirable data locality, synchronous concurrency and simple data and program structures. Its implementation on a graphics processing unit outperforms the other existing implementations for kNN search based on either sort or select operations. We provide algorithm analysis and experimental results.