One of the main goals of the STAP-BOY program has been the implementation of a space-time adaptive processing (STAP) algorithm on graphics processing units (GPUs) with the goal of reducing the processing time. Within the context of GPU implementation, we have further developed algorithms that exploit data redundancy
inherent in particular STAP applications. Integration of these algorithms with GPU architecture is of primary importance for fast algorithmic processing times. STAP algorithms involve solving a linear system in which the transformation matrix is a covariance matrix. A standard method involves estimating a covariance matrix from a data matrix, computing its Cholesky factors by one of several methods, and then solving the system by substitution. Some STAP applications have redundancy in successive data matrices from which the covariance matrices are formed. For STAP applications in which a data matrix is updated with the addition of a new data row at
the bottom and the elimination of the oldest data in the top of the matrix, a sequence of data matrices have multiple rows in common. Two methods have been developed for exploiting this type of data redundancy when computing Cholesky factors. These two methods are referred to as
1) Fast QR factorizations of successive data matrices
2) Fast Cholesky factorizations of successive covariance matrices.
We have developed GPU implementations of these two methods. We show that these two algorithms exhibit reduced computational complexity when compared to benchmark algorithms that do not exploit data redundancy. More importantly, we show that when these algorithmic improvements are optimized for the GPU architecture,
the processing times of a GPU implementation of these matrix factorization algorithms may be greatly improved.
We present experiments on the optical properties of ultrathin (a few nanometers thick) films (copperphthalocyanine, amorphous silicon) with an incorporated metal cluster film (silver, indium). Due to the spatially close interface, the plasmon absorption may be displaced from its resonance frequency in the bulk, and its average position may be controlled by the average thickness of the ultrathin optical film. For example, we observe a shift of the plasmon resonance of silver clusters in amorphous silicon films (on quartz glass) from 440 nm to 740 nm, when the silicon thickness increases from `zero' up to 15 nm. The deposition experiments are accompanied by investigation of the film structure, particularly in order to estimate the silver cluster diameter, which is around 3 nm or less. Additionally, numerical simulations are in progress to optimize the island film preparation conditions.
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