Large scale shape optimization for accelerator cavities
نویسندگان
چکیده
منابع مشابه
A limited memory adaptive trust-region approach for large-scale unconstrained optimization
This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newt...
متن کاملA HYBRID MODIFIED GENETIC-NELDER MEAD SIMPLEX ALGORITHM FOR LARGE-SCALE TRUSS OPTIMIZATION
In this paper a hybrid algorithm based on exploration power of the Genetic algorithms and exploitation capability of Nelder Mead simplex is presented for global optimization of multi-variable functions. Some modifications are imposed on genetic algorithm to improve its capability and efficiency while being hybridized with Simplex method. Benchmark test examples of structural optimization with a...
متن کاملA Data-Reuse Aware Accelerator for Large-Scale Convolutional Networks
This paper presents a clustered SIMD accelerator template for Convolutional Networks. These networks significantly outperform other methods in detection and classification tasks in the vision domain. Due to the excessive compute and data transfer requirements these applications benefit a lot from a dedicated accelerator. The proposed accelerator reduces memory traffic by loop transformations su...
متن کاملA Large-Scale Spiking Neural Network Accelerator for FPGA Systems
Spiking neural networks (SNN) aim to mimic membrane potential dynamics of biological neurons. They have been used widely in neuromorphic applications and neuroscience modeling studies. We design a parallel SNN accelerator for producing large-scale cortical simulation targeting an off-theshelf Field-Programmable Gate Array (FPGA)-based system. The accelerator parallelizes synaptic processing wit...
متن کاملLarge Scale Unconstrained Optimization
This paper reviews advances in Newton quasi Newton and conjugate gradi ent methods for large scale optimization It also describes several packages developed during the last ten years and illustrates their performance on some practical problems Much attention is given to the concept of partial separa bility which is gaining importance with the arrival of automatic di erentiation tools and of opt...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2009
ISSN: 1742-6596
DOI: 10.1088/1742-6596/180/1/012001