1.5.2.4 Architecture balance parallelism In order to achieve better parallel performance, the architecture of parallel computing must have enough processors, and adequate global memory access and interprocessor
The parallel hardware architecture for floating point matrix inversion in the embodiments of the present invention comprises: a matrix writing module, used for writing matrix data of an augmented matrix in a first memory and a second memory, the first memory and the second memory dynamically ...
However, given the nature of a P system, its execution in a computer that follows the Von Neumann architecture model is not efficient enough. Therefore, attempts have been made to achieve parallel emulation using GPUs [29], [30], [31]. However, these simulations try to reproduce similar ...
In this cross-journal collection, we aim to bring together cutting-edge research of neuromorphic architecture and hardware, computing algorithms and theories, and the related innovative applications.
Architecture of the simulated memristor-based neural processing unit and relevant circuit modules in the macro core. Extended Data Fig. 6 Scalability of the joint strategy. The joint strategy combines the hybrid training method and the parallel computing technique of replicating the same kernels. We ...
Chapter 1. An Introduction to Computer Architecture Each machine has its own, unique personality which probably could be defined as the intuitive sum total of everything you know and feel about it. This personality constantly changes, usually for the worse, but sometimes surprisingly for the ...
[6] have proposed a memory-efficient dual-scan 2-D lifting DWT architecture with temporal buffer 4Nand critical path of two multipliers and four adders. Recently, a dual-scan parallel flipping architecture is introduced with the critical path of one multiplier, less pipeline registers, and simple...
Hierarchical Networks-on-Chip Architecture for Neuromorphic HardwareThe mammalian brain has become one of the most interesting and active research topics, not only for neuroscientists, but also for computer scientists and engineers. However, whilst neuroscientists are interested in biophysical models (Trap...
In: Proceedings of the International Symposium Computer Architecture, pp. 214–224 (2000) Sohi, G., Franklin, M.: High-bandwidth data memory systems for superscalar processors. In: Proceedings of the Fourth International Conference on Architectural Support for Programming Languages and Operating ...
RPN and Fast-RCNN share most of the convolution layers, and the features from the last shared layer are used for two separate tasks (i.e. proposal generation and region classification). With this highly efficient architecture, Faster R-CNN achieves 6 FPS inference speed on a GPU and the ...