It takes the average reader 3 hours and 41 minutes to read An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation by Florian Stefan Glaser
Assuming a reading speed of 250 words per minute. Learn more
Aging population and the thereby ever-rising cost of health services call for novel and innovative solutions for providing medical care and services. So far, medical care is primarily provided in the form of time-consuming in-person appointments with trained personnel and expensive, stationary instrumentation equipment. As for many current and past challenges, the advances in microelectronics are a crucial enabler and offer a plethora of opportunities. With key building blocks such as sensing, processing, and communication systems and circuits getting smaller, cheaper, and more energy-efficient, personal and wearable or even implantable point-of-care devices with medicalgrade instrumentation capabilities become feasible. Device size and battery lifetime are paramount for the realization of such devices. Besides integrating the required functionality into as few individual microelectronic components as possible, the energy efficiency of such is crucial to reduce battery size, usually being the dominant contributor to overall device size. In this thesis, we present two major contributions to achieve the discussed goals in the context of miniaturized medical instrumentation: First, we present a synchronization solution for embedded, parallel near-threshold computing (NTC), a promising concept for enabling the required processing capabilities with an energy efficiency that is suitable for highly mobile devices with very limited battery capacity. Our proposed solution aims at increasing energy efficiency and performance for parallel NTC clusters by maximizing the effective utilization of the available cores under parallel workloads. We describe a hardware unit that enables fine-grain parallelization by greatly optimizing and accelerating core-to-core synchronization and communication and analyze the impact of those mechanisms on the overall performance and energy efficiency of an eight-core cluster. With a range of digital signal processing (DSP) applications typical for the targeted systems, the proposed hardware unit improves performance by up to 92% and 23% on average and energy efficiency by up to 98% and 39% on average. In the second part, we present a MCU processing and control subsystem (MPCS) for the integration into VivoSoC, a highly versatile single-chip solution for mobile medical instrumentation. In addition to the MPCS, it includes a multitude of analog front-ends (AFEs) and a multi-channel power management IC (PMIC) for voltage conversion. ...
An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation by Florian Stefan Glaser is 216 pages long, and a total of 55,296 words.
This makes it 73% the length of the average book. It also has 68% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 5 hours and 2 minutes to read An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation aloud.
An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation by Florian Stefan Glaser is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.
To buy An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation by Florian Stefan Glaser on Amazon click the button below.
Buy An Event-Driven Parallel-Processing Subsystem for Energy-Efficient Mobile Medical Instrumentation on Amazon