2,450 research outputs found
Design techniques for low-power systems
Portable products are being used increasingly. Because these systems are battery powered, reducing power consumption is vital. In this report we give the properties of low-power design and techniques to exploit them on the architecture of the system. We focus on: minimizing capacitance, avoiding unnecessary and wasteful activity, and reducing voltage and frequency. We review energy reduction techniques in the architecture and design of a hand-held computer and the wireless communication system including error control, system decomposition, communication and MAC protocols, and low-power short range networks
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Signal Encoding and Digital Signal Processing in Continuous Time
This work investigates signal encoding in, and architectures of, digital signal processing systems that function in continuous time (CT). Unlike conventional digital signal processors (DSPs), which rely on a clock to dictate the sampling times of an analog-to-digital converter (ADC) and to provide the tap delay timing, CT DSPs function entirely in continuous time, without a sampling or a synchronizing clock. The samples of a CT DSP system are generated and processed only when some measure of the input signal crosses a predetermined threshold. The effective sampling rate and the dynamic power dissipation of a CT digital system automatically adapt to the activity of the input signal. The properties of signals sampled in continuous time are investigated in this thesis. A technique for reducing the effective sampling rate of a CT system is presented, in which the digital signal encoding is varied by adjusting the resolution according to a property of the input. A variable-resolution system leads to a decrease in the number of samples generated, a reduction in the power dissipation and a reduction in the effective chip area of a CT DSP, all without sacrificing in-band performance. The properties of several asynchronous signal-driven sampling techniques are analyzed and compared. The architecture and signal encoding of CT DSPs for signals in the lower gigahertz frequency range are investigated, with consideration of speed and accuracy limitations in the context of submicron CMOS technologies. A per-edge digital signal encoding technique is developed, which bypasses timing problems of processing high-speed digital signals; the properties of per-edge encoded signals are discussed. The design considerations of a low-resolution per-edge-encoded gigahertz-range CT DSP are discussed and an implementation for a possible application is detailed. A prototype chip has been fabricated in ST 65 nm CMOS technology, which has a compact processor core area of 0.073 mm^2. The implemented CT digital processor achieves SNDR of over 20 dB with 3 bits of resolution and a maximum usable -3 dB bandwidth of 0.8 GHz to 3.2 GHz. The processor can be configured as a one-tap to six-tap CT FIR filter and has an active power dissipation that varies from 0.27 mW to 9.5 mW, depending on the amplitude and frequency of the input signal
Science and Applications Space Platform (SASP) End-to-End Data System Study
The capability of present technology and the Tracking and Data Relay Satellite System (TDRSS) to accommodate Science and Applications Space Platforms (SASP) payload user's requirements, maximum service to the user through optimization of the SASP Onboard Command and Data Management System, and the ability and availability of new technology to accommodate the evolution of SASP payloads were assessed. Key technology items identified to accommodate payloads on a SASP were onboard storage devices, multiplexers, and onboard data processors. The primary driver is the limited access to TDRSS for single access channels due to sharing with all the low Earth orbit spacecraft plus shuttle. Advantages of onboard data processing include long term storage of processed data until TRDSS is accessible, thus reducing the loss of data, eliminating large data processing tasks at the ground stations, and providing a more timely access to the data
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Energy-Efficient Time-Based Encoders and Digital Signal Processors in Continuous Time
Continuous-time (CT) data conversion and continuous-time digital signal processing (DSP) are an interesting alternative to conventional methods of signal conversion and processing. This alternative proposes time-based encoding that may not suffer from aliasing; shows superior spectral properties (e.g. no quantization noise floor); and enables time-based, event-driven, flexible signal processing using digital circuits, thus scaling well with technology. Despite these interesting features, this approach has so far been limited by the CT encoder, due to both its relatively poor energy efficiency and the constraints it imposes on the subsequent CT DSP. In this thesis, we present three principles that address these limitations and help improve the CT ADC/DSP system.
First, an adaptive-resolution encoding scheme that achieves first-order reconstruction with simple circuitry is proposed. It is shown that for certain signals, the scheme can significantly reduce the number of samples generated per unit of time for a given accuracy compared to schemes based on zero-order-hold reconstruction, thus promising to lead to low dynamic power dissipation at the system level.
Presented next is a novel time-based CT ADC architecture, and associated encoding scheme, that allows a compact, energy-efficient circuit implementation, and achieves first-order quantization error spectral shaping. The design of a test chip, implemented in a 0.65-V 28-nm FDSOI process, that includes this CT ADC and a 10-tap programmable FIR CT DSP to process its output is described. The system achieves 32 dB â 42 dB SNDR over a 10 MHz â 50 MHz bandwidth, occupies 0.093 mm2, and dissipates 15 ”Wâ163 ”W as the input amplitude goes from zero to full scale.
Finally, an investigation into the possibility of CT encoding using voltage-controlled oscillators is undertaken, and it leads to a CT ADC/DSP system architecture composed primarily of asynchronous digital delays. The latter makes the system highly digital and technology-scaling-friendly and, hence, is particularly attractive from the point of view of technology migration. The design of a test chip, where this delay-based CT ADC/DSP system architecture is used to implement a 16-tap programmable FIR filter, in a 1.2-V 28-nm FDSOI process, is described. Simulations show that the system will achieve a 33 dB â 40 dB SNDR over a 600 MHz bandwidth, while dissipating 4 mW
The 30/20 GHz flight experiment system, phase 2. Volume 2: Experiment system description
A detailed technical description of the 30/20 GHz flight experiment system is presented. The overall communication system is described with performance analyses, communication operations, and experiment plans. Hardware descriptions of the payload are given with the tradeoff studies that led to the final design. The spacecraft bus which carries the payload is discussed and its interface with the launch vehicle system is described. Finally, the hardwares and the operations of the terrestrial segment are presented
Principles of Neuromorphic Photonics
In an age overrun with information, the ability to process reams of data has
become crucial. The demand for data will continue to grow as smart gadgets
multiply and become increasingly integrated into our daily lives.
Next-generation industries in artificial intelligence services and
high-performance computing are so far supported by microelectronic platforms.
These data-intensive enterprises rely on continual improvements in hardware.
Their prospects are running up against a stark reality: conventional
one-size-fits-all solutions offered by digital electronics can no longer
satisfy this need, as Moore's law (exponential hardware scaling),
interconnection density, and the von Neumann architecture reach their limits.
With its superior speed and reconfigurability, analog photonics can provide
some relief to these problems; however, complex applications of analog
photonics have remained largely unexplored due to the absence of a robust
photonic integration industry. Recently, the landscape for
commercially-manufacturable photonic chips has been changing rapidly and now
promises to achieve economies of scale previously enjoyed solely by
microelectronics.
The scientific community has set out to build bridges between the domains of
photonic device physics and neural networks, giving rise to the field of
\emph{neuromorphic photonics}. This article reviews the recent progress in
integrated neuromorphic photonics. We provide an overview of neuromorphic
computing, discuss the associated technology (microelectronic and photonic)
platforms and compare their metric performance. We discuss photonic neural
network approaches and challenges for integrated neuromorphic photonic
processors while providing an in-depth description of photonic neurons and a
candidate interconnection architecture. We conclude with a future outlook of
neuro-inspired photonic processing.Comment: 28 pages, 19 figure
Energy Aware Runtime Systems for Elastic Stream Processing Platforms
Following an invariant growth in the required computational performance of processors, the multicore revolution started around 20 years ago. This revolution was mainly an answer to power dissipation constraints restricting the increase of clock frequency in single-core processors. The multicore revolution not only brought in the challenge of parallel programming, i.e. being able to develop software exploiting the entire capabilities of manycore architectures, but also the challenge of programming heterogeneous platforms. The question of âon which processing element to map a specific computational unit?â, is well known in the embedded community. With the introduction of general-purpose graphics processing units (GPGPUs), digital signal processors (DSPs) along with many-core processors on different system-on-chip platforms, heterogeneous parallel platforms are nowadays widespread over several domains, from consumer devices to media processing platforms for telecom operators. Finding mapping together with a suitable hardware architecture is a process called design-space exploration. This process is very challenging in heterogeneous many-core architectures, which promise to offer benefits in terms of energy efficiency. The main problem is the exponential explosion of space exploration. With the recent trend of increasing levels of heterogeneity in the chip, selecting the parameters to take into account when mapping software to hardware is still an open research topic in the embedded area. For example, the current Linux scheduler has poor performance when mapping tasks to computing elements available in hardware. The only metric considered is CPU workload, which as was shown in recent work does not match true performance demands from the applications. Doing so may produce an incorrect allocation of resources, resulting in a waste of energy. The origin of this research work comes from the observation that these approaches do not provide full support for the dynamic behavior of stream processing applications, especially if these behaviors are established only at runtime. This research will contribute to the general goal of developing energy-efficient solutions to design streaming applications on heterogeneous and parallel hardware platforms. Streaming applications are nowadays widely spread in the software domain. Their distinctive characiteristic is the retrieving of multiple streams of data and the need to process them in real time. The proposed work will develop new approaches to address the challenging problem of efficient runtime coordination of dynamic applications, focusing on energy and performance management.Efter en oförĂ€nderlig tillvĂ€xt i prestandakrav hos processorer, började den flerkĂ€rniga processor-revolutionen för ungefĂ€r 20 Ă„r sedan. Denna revolution skedde till största del som en lösning till begrĂ€nsningar i energieffekten allt eftersom klockfrekvensen kontinuerligt höjdes i en-kĂ€rniga processorer. Den flerkĂ€rniga processor-revolutionen medförde inte enbart utmaningen gĂ€llande parallellprogrammering, m.a.o. förmĂ„gan att utveckla mjukvara som anvĂ€nder sig av alla delelement i de flerkĂ€rniga processorerna, men ocksĂ„ utmaningen med programmering av heterogena plattformar. FrĂ„gestĂ€llningen âpĂ„ vilken processorelement skall en viss berĂ€kning utföras?â Ă€r vĂ€l kĂ€nt inom ramen för inbyggda datorsystem. Efter introduktionen av grafikprocessorer för allmĂ€nna berĂ€kningar (GPGPU), signalprocesserings-processorer (DSP) samt flerkĂ€rniga processorer pĂ„ olika system-on-chip plattformar, Ă€r heterogena parallella plattformar idag omfattande inom mĂ„nga domĂ€ner, frĂ„n konsumtionsartiklar till mediaprocesseringsplattformar för telekommunikationsoperatörer. Processen att placera berĂ€kningarna pĂ„ en passande hĂ„rdvaruplattform kallas för utforskning av en designrymd (design-space exploration). Denna process Ă€r mycket utmanande för heterogena flerkĂ€rniga arkitekturer, och kan medföra fördelar nĂ€r det gĂ€ller energieffektivitet. Det största problemet Ă€r att de olika valmöjligheterna i designrymden kan vĂ€xa exponentiellt. Enligt den nuvarande trenden som förespĂ„r ökad heterogeniska aspekter i processorerna Ă€r utmaningen att hitta den mest passande placeringen av berĂ€kningarna pĂ„ hĂ„rdvaran Ă€nnu en forskningsfrĂ„ga inom ramen för inbyggda datorsystem. Till exempel, den nuvarande schemalĂ€ggaren i Linux operativsystemet Ă€r inkapabel att hitta en effektiv placering av berĂ€kningarna pĂ„ den underliggande hĂ„rdvaran. Det enda mĂ€tsĂ€ttet som anvĂ€nds Ă€r processorns belastning vilket, som visats i tidigare forskning, inte motsvarar den verkliga prestandan i applikationen. AnvĂ€ndning av detta mĂ€tsĂ€tt vid resursallokering resulterar i slöseri med energi. Denna forskning hĂ€rstammar frĂ„n observationerna att dessa tillvĂ€gagĂ„ngssĂ€tt inte stöder det dynamiska beteendet hos ström-processeringsapplikationer (stream processing applications), speciellt om beteendena bara etableras vid körtid. Denna forskning kontribuerar till det allmĂ€nna mĂ„let att utveckla energieffektiva lösningar för ström-applikationer (streaming applications) pĂ„ heterogena flerkĂ€rniga hĂ„rdvaruplattformar. Ström-applikationer Ă€r numera mycket vanliga i mjukvarudomĂ€n. Deras distinkta karaktĂ€r Ă€r inlĂ€sning av flertalet dataströmmar, och behov av att processera dem i realtid. Arbetet i denna forskning understöder utvecklingen av nya sĂ€tt för att lösa det utmanade problemet att effektivt koordinera dynamiska applikationer i realtid och fokus pĂ„ energi- och prestandahantering
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