The Design and Implement of SSD Chip with Multi-Bus and 8 Channels

2011 ◽  
Vol 58-60 ◽  
pp. 2592-2596 ◽  
Author(s):  
Zhi Lou Yu ◽  
Ji Hua ◽  
Li Feng
Keyword(s):  
Data Transmission ◽  
High Performance ◽  
Garbage Collection ◽  
Reading Speed ◽  
Parallel Operation ◽  
Performance Requirements ◽  
Solid State Disk ◽  
Wear And Tear ◽  
And Performance ◽  
Arm7 Processor

As networks and the development of information technology, the traditional machinery hard in some areas has been unable to satisfy the speed and performance requirements, and appeared SSD（solid state disk）. This article describes the design of a high-performance SSD control chip,the SSD control chip intergrate internal ARM7 processor, by AHB bus to rapid implement the dma data transmission, the interface with nandflash adopted eight, which can achieve on the parallel operation and improve nandflash interface speed. With the host interface uses sata2.Firmware use of the FTL algorithms, including and of the operation of the mapping. A balanced mix of wear and tear, a bad piece of management and garbage collection, and more efficient to access to SSD, improved ssd life. That the SSD chip for reading speed 200MB/S, the maximum writing speed is 140MB/s.

Nonlinear Compensation for High Performance Feedback Systems With Actuator Imperfections

2013 ◽  
Author(s):  
Cameron L. Mock ◽  
Zachary T. Hamilton ◽  
Dustin Carruthers ◽  
John F. O’Brien
Keyword(s):  
Performance Feedback ◽  
High Performance ◽  
Vibration Suppression ◽  
Actuator Saturation ◽  
Design Method ◽  
Nonlinear Feedback ◽  
Feedback Systems ◽  
Performance Requirements ◽  
Common Causes ◽  
And Performance

Measures to reduce control performance for greater robustness (e.g. reduced bandwidth, shallow loop roll-off) must be enhanced if the plant or actuators are known to have nonlinear characteristics that cause variations in loop transmission. Common causes of these nonlinear behaviors are actuator saturation and friction/stiction in the moving parts of mechanical systems. Systems with these characteristics that also have stringent closed loop performance requirements present the control designer with an extremely challenging problem. A design method for these systems is presented that combines very aggressive Nyquist-stable linear control to provide large negative feedback with nonlinear feedback to compensate for the effects of multiple nonlinearities in the loop that threaten stability and performance. The efficacy of this approach is experimentally verified on a parallel kinematic mechanism with multiple uncertain nonlinearities used for vibration suppression.

scholarly journals Design of a Clutchless Hybrid Transmission for a High-Performance Vehicle

2015 ◽  
Author(s):  
Chad L. Jacoby ◽  
Young Suk Jo ◽  
Jake Jurewicz ◽  
Guillermo Pamanes ◽  
Joshua E. Siegel ◽  
...  
Keyword(s):  
High Performance ◽  
Power Flow ◽  
Combustion Engine ◽  
Performance Requirements ◽  
Wide Range ◽  
Friction Clutch ◽  
Hybrid Transmission ◽  
And Performance ◽  
Electrical Motors ◽  
Operational Modes

There exists the potential for major simplifications to current hybrid transmission architectures, which can lead to advances in powertrain performance. This paper assesses the technical merits of various hybrid powertrains in the context of high-performance vehicles and introduces a new transmission concept targeted at high performance hybrid applications. While many hybrid transmission configurations have been developed and implemented in mainstream and even luxury vehicles, ultra high performance sports cars have only recently begun to hybridize. The unique performance requirements of such vehicles place novel constraints on their transmissions designs. The goals become less about improved efficiency and smoothness and more centered on weight reduction, complexity reduction, and performance improvement. To identify the most critical aspects of a high performance transmission, a wide range of existing technologies is studied in concert with basic physical performance analysis of electrical motors and an internal combustion engine. The new transmission concepts presented here emphasize a reduction in inertial, frictional, and mechanical losses. A series of conceptual powertrain designs are evaluated against the goals of reducing mechanical complexity and maintaining functionality. The major innovation in these concepts is the elimination of a friction clutch to engage and disengage gears. Instead, the design proposes that the inclusion of a large electric motor enables the gears to be speed-matched and torque-zeroed without the inherent losses associated with a friction clutch. Additionally, these transmission concepts explore the merits of multiple electric motors and their placement as well as the reduction in synchronization interfaces. Ultimately, two strategies for speed-matched gear sets are considered, and a speed-matching prototype of the chosen methodology is presented to validate the feasibility of the proposed concept. The power flow and operational modes of both transmission architectures are studied to ensure required functionality and identify further areas of optimization. While there are still many unanswered questions about this concept, this paper introduces the base analysis and proof of concept for a technology that has great potential to advance hybrid vehicles at all levels.

FLASH: F ast Neura l A rchitecture S earch with H ardware Optimization

2021 ◽  
Vol 20 (5s) ◽  
pp. 1-26
Author(s):  
Guihong Li ◽  
Sumit K. Mandal ◽  
Umit Y. Ogras ◽  
Radu Marculescu
Keyword(s):  
Energy Consumption ◽  
High Performance ◽  
Search Space ◽  
Analytical Models ◽  
Raspberry Pi ◽  
Simplicial Homology ◽  
Theoretical Contribution ◽  
Standard Ml ◽  
Performance Requirements ◽  
And Performance

Neural architecture search (NAS) is a promising technique to design efficient and high-performance deep neural networks (DNNs). As the performance requirements of ML applications grow continuously, the hardware accelerators start playing a central role in DNN design. This trend makes NAS even more complicated and time-consuming for most real applications. This paper proposes FLASH, a very fast NAS methodology that co-optimizes the DNN accuracy and performance on a real hardware platform. As the main theoretical contribution, we first propose the NN-Degree, an analytical metric to quantify the topological characteristics of DNNs with skip connections (e.g., DenseNets, ResNets, Wide-ResNets, and MobileNets). The newly proposed NN-Degree allows us to do training-free NAS within one second and build an accuracy predictor by training as few as 25 samples out of a vast search space with more than 63 billion configurations. Second, by performing inference on the target hardware, we fine-tune and validate our analytical models to estimate the latency, area, and energy consumption of various DNN architectures while executing standard ML datasets. Third, we construct a hierarchical algorithm based on simplicial homology global optimization (SHGO) to optimize the model-architecture co-design process, while considering the area, latency, and energy consumption of the target hardware. We demonstrate that, compared to the state-of-the-art NAS approaches, our proposed hierarchical SHGO-based algorithm enables more than four orders of magnitude speedup (specifically, the execution time of the proposed algorithm is about 0.1 seconds). Finally, our experimental evaluations show that FLASH is easily transferable to different hardware architectures, thus enabling us to do NAS on a Raspberry Pi-3B processor in less than 3 seconds.

scholarly journals Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System

2020 ◽  
Vol 184 ◽  
pp. 01102
Author(s):  
P Magudeaswaran. ◽  
C. Vivek Kumar ◽  
Rathod Ravinder
Keyword(s):  
Fuzzy Inference System ◽  
High Performance ◽  
Fuzzy Inference ◽  
High Performance Concrete ◽  
Intelligent System ◽  
Computing Methods ◽  
Inference System ◽  
Performance Requirements ◽  
Neuro Fuzzy ◽  
And Performance

High-Performance Concrete (HPC) is a high-quality concrete that requires special conformity and performance requirements. The objective of this study was to investigate the possibilities of adapting neural expert systems like Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a simulator and intelligent system and to predict durability and strength of HPC composites. These soft computing methods emulate the decision-making ability of human expert benefits both the construction industry and the research community. These new methods, if properly utilized, have the potential to increase speed, service life, efficiency, consistency, minimizes errors, saves time and cost which would otherwise be squandered using the conventional approaches.

scholarly journals Forecasting of strength and durability properties of High Performance Composites by Artificial Neural Networks (ANN)

2020 ◽  
Vol 184 ◽  
pp. 01103
Author(s):  
Magudeaswaran. P ◽  
Vivek Kumar C ◽  
Britto Jeyakumar M S
Keyword(s):  
High Performance ◽  
High Performance Concrete ◽  
Intelligent System ◽  
Computing Methods ◽  
Performance Requirements ◽  
Soft Computing Methods ◽  
Artificial Neural ◽  
And Performance ◽  
Artificial Neural Network Ann ◽  
Strength And Durability

High Performance Concrete (HPC) is the high quality concrete that requires special conformity and performance requirements. The objective of this study was to investigate the possibilities of adapting neural expert system like Artificial Neural Network (ANN) in the development of simulator and intelligent system and to predict durability and strength of HPC composites. This soft computing methods emulates the decision-making ability of a human expert benefits both the construction industry and the research community. These new methods, if properly utilized, have the potential to increase speed, service life, efficiency, consistency, minimizes errors, saves time and cost which would otherwise be squandered using the conventional approaches.

Trace nanoanalysis

1994 ◽  
Vol 52 ◽  
pp. 940-941
Author(s):  
D. E. Newbury ◽  
R. D. Leapman
Keyword(s):  
High Performance ◽  
Secondary Ion Mass Spectrometry ◽  
Detection Efficiency ◽  
Volume Element ◽  
And Performance ◽  
Trace Constituents ◽  
Secondary Ion ◽  
Concentration Levels ◽  
Structure Properties

Trace constituents, which can be very loosely defined as those present at concentration levels below 1 percent, often exert influence on structure, properties, and performance far greater than what might be estimated from their proportion alone. Defining the role of trace constituents in the microstructure, or indeed even determining their location, makes great demands on the available array of microanalytical tools. These demands become increasingly more challenging as the dimensions of the volume element to be probed become smaller. For example, a cubic volume element of silicon with an edge dimension of 1 micrometer contains approximately 5×1010 atoms. High performance secondary ion mass spectrometry (SIMS) can be used to measure trace constituents to levels of hundreds of parts per billion from such a volume element (e. g., detection of at least 100 atoms to give 10% reproducibility with an overall detection efficiency of 1%, considering ionization, transmission, and counting).

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