scholarly journals A MPI + OpenMP + CUDA Hybrid Parallel Scheme for MT Occam Inversion

2016 ◽  
Vol 9 (9) ◽  
pp. 67-82 ◽  
Author(s):  
Yu Liu ◽  
Renhao Xiong ◽  
Renhao Xiong
Author(s):  
Meng Yang ◽  
Bian Wu ◽  
Chi Fan ◽  
Han-Yu Xie ◽  
Jian-Zhong Chen ◽  
...  
Keyword(s):  

Quantum ◽  
2017 ◽  
Vol 1 ◽  
pp. 27 ◽  
Author(s):  
Pavel Sekatski ◽  
Michalis Skotiniotis ◽  
Janek Kołodyński ◽  
Wolfgang Dür

We establish general limits on how precise a parameter, e.g. frequency or the strength of a magnetic field, can be estimated with the aid of full and fast quantum control. We consider uncorrelated noisy evolutions of N qubits and show that fast control allows to fully restore the Heisenberg scaling (~1/N^2) for all rank-one Pauli noise except dephasing. For all other types of noise the asymptotic quantum enhancement is unavoidably limited to a constant-factor improvement over the standard quantum limit (~1/N) even when allowing for the full power of fast control. The latter holds both in the single-shot and infinitely-many repetitions scenarios. However, even in this case allowing for fast quantum control helps to increase the improvement factor. Furthermore, for frequency estimation with finite resource we show how a parallel scheme utilizing any fixed number of entangled qubits but no fast quantum control can be outperformed by a simple, easily implementable, sequential scheme which only requires entanglement between one sensing and one auxiliary qubit.


Author(s):  
Nilda G. Villanueva-Chacón ◽  
Edgar A. Martínez-García

A highly concurrent task-planner for distributed multi-robot systems in dynamical industrial feed-lines is presented in this chapter. The system deals with two main issues: a) a path-planning model and b) a robotic-tasks scheduler. A set of kinematic control laws based on directional derivatives model the dynamical robots interaction. Distributed wheeled mobile robots perform the execution of autonomous tasks concurrently and synchronized just in time. A planner model for distributed tasks to autonomously reconfigure and synchronize online change priority missions by the robotic primitives—sense, plan, and act—are proposed. The robotic tasks concern carry-and-fetch to different goals, and dispatching materials. Numerical simulation of mathematical formulation and real experiments illustrate the parallel computing capability and the distributed robot's behavior. Results depict robots dealing with highly concurrent tasks and dynamical events through a parallel scheme.


2019 ◽  
Vol 16 (07) ◽  
pp. 1950038 ◽  
Author(s):  
S. H. Ju ◽  
H. H. Hsu

An out-of-core block Lanczos method with the OpenMP parallel scheme was developed to solve large spare damped eigenproblems. The symmetric generalized eigenproblem is first solved using the block Lanczos method with the preconditioned conjugate gradient (PCG) method, and the condensed damped eigenproblem is then solved to obtain the complex eigenvalues. Since the PCG solvers and out-of-core schemes are used, a large-scale eigenproblem can be solved using minimal computer memory. The out-of-core arrays only need to be read once in each Lanczos iteration, so the proposed method requires little extra CPU time. In addition, the second-level OpenMP parallel computation in the PCG solver is suggested to avoid using a large block size that often increases the number of iterations needed to achieve convergence.


Author(s):  
Qing Wu ◽  
Colin Cole

Conventionally, force elements in longitudinal train dynamics (LTD) are determined sequentially. Actually, all these force elements are independent from each other, i.e., determination of each one does not require inputs from others. This independent feature makes LTD feasible for parallel computing. A parallel scheme has been proposed and compared with the conventional sequential scheme in regard to computational efficiency. The parallel scheme is tested as not suitable for LTD; computing time of the parallel scheme is about 165% of the sequential scheme on a four-CPU personal computer (PC). A modified parallel scheme named the hybrid scheme was then proposed. The computing time of the hybrid scheme is only 70% of the sequential scheme. The other advantage of the hybrid scheme is that only two processors are required, which means the hybrid scheme can be implemented on PCs.


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