The Super Instruction Architecture (SIA) was developed to support parallel implementation of algorithms for electronic structure computational chemistry calculations. The methods are programmed in a domain specific pr...
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ISBN:
(纸本)9781605584980
The Super Instruction Architecture (SIA) was developed to support parallel implementation of algorithms for electronic structure computational chemistry calculations. The methods are programmed in a domain specific programming language called Super Instruction Assembly Language (SIAL). An important novel aspect of SIAL is that algorithms axe expressed in terms of operations (super instructions) on blocks (super numbers) rather than individual floating point numbers. The bytecode from compiled SIAL programs is executed by a parallel virtual machine known as the Super Instruction Processor (SIP). Compute intensive operations such as tensor contractions and diagonalizations, as well as communication and I/O are handled by the SIP. By separating the algorithmic complexity of the application domain in SIAL from the complexities of parallel execution on computer hardware in the SIP, a software system has been created that allows for very effective optimization and tuning on different hardware architectures with quite manageable effort.
An open-loop (OL) method to enable distributed transmit beamforming is presented in this paper. The approach eliminates the need for feedback to distant receive nodes by using multiple tones to set a coherent phase ac...
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An open-loop (OL) method to enable distributed transmit beamforming is presented in this paper. The approach eliminates the need for feedback to distant receive nodes by using multiple tones to set a coherent phase across the distributed array. This arrangement is able to constantly keep the array synchronized to avoid the frequency drifting of the local oscillators (LOs) equipped by distributed communication nodes, even while transmit beamforming is taking place. This is made possible because the synchronization is achieved through radio frequency (RF) carriers at frequencies other than the beamforming frequency. This enables uninterrupted beamforming, which is not possible in previous carrier synchronization algorithms due to half-duplex limitation. The noise performance of the proposed scheme is also presented. (C) 2021 Elsevier B.V. All rights reserved.
In the framework of fully permutable loops, tiling has been studied extensively as a source-to-source program transformation. We build upon recent results by Hogsted, Carter, and Ferrante [12], who aimed at determinin...
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In the framework of fully permutable loops, tiling has been studied extensively as a source-to-source program transformation. We build upon recent results by Hogsted, Carter, and Ferrante [12], who aimed at determining the cumulated idle time spent by all processors while executing the partitioned (tiled) computation domain. We propose new, much shorter proofs of all their results and extend these in several important directions. More precisely, we provide an accurate solution for all values of the rise parameter that relates the shape of the iteration space to that of the tiles, and for all possible distributions of the tiles to processors. In contrast, the authors in [12] dealt only with a limited number of cases and provided upper bounds rather than exact formulas.
A scenario with multiple talkers and additive background noise is considered, where some talkers are active simultaneously and the activity of the talkers changes with time. We propose an MMSE-based method to blindly ...
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ISBN:
(纸本)9781479903573
A scenario with multiple talkers and additive background noise is considered, where some talkers are active simultaneously and the activity of the talkers changes with time. We propose an MMSE-based method to blindly extract any talker using bin-wise position estimates obtained from distributed microphone arrays. In order to distinguish between different talkers, the position estimates are clustered using the expectation maximization algorithm. The resulting posterior probabilities allow to estimate the PSD matrices of the talkers and compute an MMSE-optimal linear filter for extracting each talker. We evaluate the performance of the proposed method in terms of noise and interference reduction and distortion of the desired speech signal at the output of a multichannel Wiener filter.
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