The process of updating weights is one training iteration involving backpropagation. The latter can be broken down into 4 distinct steps:
In this first training step, the intention is to extract weight from the first pass of the training data into the neural network.
The training loss (precision) is calculated from a loss function, e.g mean square error. On the first iteration, the loss will be high. Then, iteration after iteration, the neural network learns and the training loss (difference) between the prediction label and training label decreases.
To achieve a minimum loss, the weights need to be adjusted by taking a derivative of the loss with respect to the weights.
The weights of each layer are then updated accordingly with the calculated weights from the training iterations.
Quick news about the development of VHDL language.
It seems that the IEEE P1076 VHDL Standards Working Group has been busy preparing VHDL-2017. It is said that it is almost ready and it is time for the VHDL community to prepare to ballot. Voting on the upcoming standard will be conducted between May and July 2017.
Since Cadence added Azuro’s ccopt by default in SOC Encounter, I think it is time to look deeper in this clock concurrent optimization. The latter was initiated by a company called Azuro which was then acquired by Cadence in July 2012.
Clock concurrent optimization merges clock tree synthesis (CTS) with physical optimization, simultaneously building clocks and optimizing logic delays based directly on a propagated clocks model of timing. Thus, the clock tree synthesis (CTS) becomes timing-driven and tightly coupled with placement and logic sizing. This is different from traditional techniques of sequential optimization and useful skew.
CTS is done by combining the benefits of pre-route layer-aware optimization and useful skewing.
Buffer insertion is not only done to just reduce the skew but also to do time borrowing and to improve the overall speed of the design.
What is the benefits of using CCopt ?
Increased chip speed or reduced chip area and power