Memory Optimization Techniques for Computing Discrete Logarithms in Compressed SIKE

2021 ◽  
pp. 296-315
Author(s):  
Aaron Hutchinson ◽  
Koray Karabina ◽  
Geovandro Pereira
Keyword(s):  
Optimization Techniques ◽  
Memory Optimization ◽  
Discrete Logarithms

scholarly journals Memory Optimization Techniques in Neural Networks: A Review

2021 ◽  
Vol 10 (6) ◽  
pp. 44-48
Author(s):  
Pratheeksha P ◽  
◽  
Pranav B M ◽  
Dr. Azra Nasreen ◽  
◽  
...  
Keyword(s):  
Neural Networks ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Model Complexity ◽  
Batch Size ◽  
Network Architectures ◽  
Memory Optimization ◽  
Memory Consumption ◽  
Reduction Techniques ◽  
Complex Models

Deep neural networks have been continuously evolving towards larger and more complex models to solve challenging problems in the field of AI. The primary bottleneck that restricts new network architectures is memory consumption. Running or training DNNs heavily relies on the hardware (CPUs, GPUs, or FPGA) which are either inadequate in terms of memory or hard-to-extend. This would further make it difficult to scale. In this paper, we review some of the latest memory footprint reduction techniques which would enable faster low model complexity. Additionally, it improves accuracy by increasing the batch size and developing wider and deeper neural networks with the same set of hardware resources. The paper emphasizes on memory optimization methods specific to CNN and RNN training.

Data and memory optimization techniques for embedded systems

2001 ◽  
Vol 6 (2) ◽  
pp. 149-206 ◽  
Author(s):  
P. R. Panda ◽  
F. Catthoor ◽  
N. D. Dutt ◽  
K. Danckaert ◽  
E. Brockmeyer ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Optimization Techniques ◽  
Memory Optimization

Review on the aerodynamics of intermediate compressor duct

2020 ◽  
Vol 14 (4) ◽  
pp. 7446-7468
Author(s):  
Manish Sharma ◽  
Beena D. Baloni
Keyword(s):  
High Pressure ◽  
Pressure Loss ◽  
Flow Analysis ◽  
Outer Wall ◽  
Optimization Techniques ◽  
Optimum Pressure ◽  
Research Areas ◽  
Static Pressure Distribution ◽  
High Pressure Compressor ◽  
Pressure Compressor

In a turbofan engine, the air is brought from the low to the high-pressure compressor through an intermediate compressor duct. Weight and design space limitations impel to its design as an S-shaped. Despite it, the intermediate duct has to guide the flow carefully to the high-pressure compressor without disturbances and flow separations hence, flow analysis within the duct has been attractive to the researchers ever since its inception. Consequently, a number of researchers and experimentalists from the aerospace industry could not keep themselves away from this research. Further demand for increasing by-pass ratio will change the shape and weight of the duct that uplift encourages them to continue research in this field. Innumerable studies related to S-shaped duct have proven that its performance depends on many factors like curvature, upstream compressor’s vortices, swirl, insertion of struts, geometrical aspects, Mach number and many more. The application of flow control devices, wall shape optimization techniques, and integrated concepts lead a better system performance and shorten the duct length.  This review paper is an endeavor to encapsulate all the above aspects and finally, it can be concluded that the intermediate duct is a key component to keep the overall weight and specific fuel consumption low. The shape and curvature of the duct significantly affect the pressure distortion. The wall static pressure distribution along the inner wall significantly higher than that of the outer wall. Duct pressure loss enhances with the aggressive design of duct, incursion of struts, thick inlet boundary layer and higher swirl at the inlet. Thus, one should focus on research areas for better aerodynamic effects of the above parameters which give duct design with optimum pressure loss and non-uniformity within the duct.

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