Low power predictable memory and processing architectures

Great demand in power optimized devices shows promising economic potential and draws lots of attention in industry and research area. Due to the continuously shrinking CMOS process, not only dynamic power but also static power has emerged as a big concern in power reduction. Other than power optimization, average-case power estimation is quite significant for power budget allocation but also challenging in terms of time and effort. In this thesis, we will introduce a methodology to support modular quantitative analysis in order to estimate average power of circuits, on the basis of two concepts named Random Bag Preserving and Linear Compositionality. It can shorten simulation time and sustain high accuracy, resulting in increasing the feasibility of power estimation of big systems. For power saving, firstly, we take advantages of the low power characteristic of adiabatic logic and asynchronous logic to achieve ultra-low dynamic and static power. We will propose two memory cells, which could run in adiabatic and non-adiabatic mode. About 90% dynamic power can be saved in adiabatic mode when compared to other up-to-date designs. About 90% leakage power is saved. Secondly, a novel logic, named Asynchronous Charge Sharing Logic (ACSL), will be introduced. The realization of completion detection is simplified considerably. Not just the power reduction improvement, ACSL brings another promising feature in average power estimation called data-independency where this characteristic would make power estimation effortless and be meaningful for modular quantitative average case analysis. Finally, a new asynchronous Arithmetic Logic Unit (ALU) with a ripple carry adder implemented using the logically reversible/bidirectional characteristic exhibiting ultra-low power dissipation with sub-threshold region operating point will be presented. The proposed adder is able to operate multi-functionally.

Irish occupational therapists' views of electronic assistive technology

Introduction: Electronic assistive technology (EAT) includes computers, environmental control systems and information technology systems and is widely considered to be an important part of present-day life. Method: Fifty-six Irish community occupational therapists completed a questionnaire on EAT. All surveyed were able to identify the benefits of EAT. Results: While respondents reported that they should be able to assess for and prescribe EATs, only a third (19) were able to do so, and half (28) had not been able to do so in the past. Community occupational therapists identified themselves as havinga role in a multidisciplinary team to assess for and prescribe EAT. Conclusion: Results suggest that it is important for occupational therapists to have up-to-date knowledge and training in assistive and computer technologies in order to respond to the occupational needs of clients.