13 research outputs found
Low Power Processor Architectures and Contemporary Techniques for Power Optimization – A Review
The technological evolution has increased the number of transistors for a given die area significantly and increased the switching speed from few MHz to GHz range. Such inversely proportional decline in size and boost in performance consequently demands shrinking of supply voltage and effective power dissipation in chips with millions of transistors. This has triggered substantial amount of research in power reduction techniques into almost every aspect of the chip and particularly the processor cores contained in the chip. This paper presents an overview of techniques for achieving the power efficiency mainly at the processor core level but also visits related domains such as buses and memories. There are various processor parameters and features such as supply voltage, clock frequency, cache and pipelining which can be optimized to reduce the power consumption of the processor. This paper discusses various ways in which these parameters can be optimized. Also, emerging power efficient processor architectures are overviewed and research activities are discussed which should help reader identify how these factors in a processor contribute to power consumption. Some of these concepts have been already established whereas others are still active research areas. © 2009 ACADEMY PUBLISHER
A Future for Integrated Diagnostic Helping
International audienceMedical systems used for exploration or diagnostic helping impose high applicative constraints such as real time image acquisition and displaying. A large part of computing requirement of these systems is devoted to image processing. This chapter provides clues to transfer consumers computing architecture approaches to the benefit of medical applications. The goal is to obtain fully integrated devices from diagnostic helping to autonomous lab on chip while taking into account medical domain specific constraints.This expertise is structured as follows: the first part analyzes vision based medical applications in order to extract essentials processing blocks and to show the similarities between consumer’s and medical vision based applications. The second part is devoted to the determination of elementary operators which are mostly needed in both domains. Computing capacities that are required by these operators and applications are compared to the state-of-the-art architectures in order to define an efficient algorithm-architecture adequation. Finally this part demonstrates that it's possible to use highly constrained computing architectures designed for consumers handled devices in application to medical domain. This is based on the example of a high definition (HD) video processing architecture designed to be integrated into smart phone or highly embedded components. This expertise paves the way for the industrialisation of intergraded autonomous diagnostichelping devices, by showing the feasibility of such systems. Their future use would also free the medical staff from many logistical constraints due the deployment of today’s cumbersome systems
System level modeling of dynamic reconfigurable system-on-chip
In this paper methods of dynamically reconfigurable multi-core System-on-chip (SoC) design are discussed, the approaches of system modeling for evaluation of these systems are presented. The dynamically reconfigurable SoC can be developed using the FPGA and the ASIC technologies. The implementations of dynamic reconfiguration using these approaches are essentially different. The system level modeling is used to evaluate the performance of dynamically reconfigured systems in the early stage of their development. The models of dynamically reconfigurable systems have very significant differences from the models of systems without a dynamical reconfiguration. The development of such models may require extensions of existing tools and specification of mechanisms functionality. In this paper the existing tools for SoC system design and the requirements for it to allow modeling of reconfigurable systems are considered. We propose mechanisms for system level modeling of the dynamically reconfigurable Networks-on-Chip (NoC) implemented on the ASIC technology
Dynamically reconfigurable asynchronous processor
The main design requirements for today's mobile applications are:
· high throughput performance.
· high energy efficiency.
· high programmability.
Until now, the choice of platform has often been limited to Application-Specific
Integrated Circuits (ASICs), due to their best-of-breed performance and power
consumption. The economies of scale possible with these high-volume markets have
traditionally been able to hide the high Non-Recurring Engineering (NRE) costs
required for designing and fabricating new ASICs. However, with the NREs and
design time escalating with each generation of mobile applications, this practice may
be reaching its limit.
Designers today are looking at programmable solutions, so that they can respond
more rapidly to changes in the market and spread costs over several generations of
mobile applications. However, there have been few feasible alternatives to ASICs:
Digital Signals Processors (DSPs) and microprocessors cannot meet the throughput
requirements, whereas Field-Programmable Gate Arrays (FPGAs) require too much
area and power.
Coarse-grained dynamically reconfigurable architectures offer better solutions for
high throughput applications, when power and area considerations are taken into
account. One promising example is the Reconfigurable Instruction Cell Array
(RICA). RICA consists of an array of cells with an interconnect that can be
dynamically reconfigured on every cycle. This allows quite complex datapaths to be
rendered onto the fabric and executed in a single configuration - making these
architectures particularly suitable to stream processing. Furthermore, RICA can be
programmed from C, making it a good fit with existing design methodologies.
However the RICA architecture has a drawback: poor scalability in terms of area and
power. As the core gets bigger, the number of sequential elements in the array must
be increased significantly to maintain the ability to achieve high throughputs through
pipelining. As a result, a larger clock tree is required to synchronise the increased
number of sequential elements. The clock tree therefore takes up a larger percentage
of the area and power consumption of the core.
This thesis presents a novel Dynamically Reconfigurable Asynchronous Processor
(DRAP), aimed at high-throughput mobile applications. DRAP is based on the RICA
architecture, but uses asynchronous design techniques - methods of designing digital
systems without clocks. The absence of a global clock signal makes DRAP more
scalable in terms of power and area overhead than its synchronous counterpart.
The DRAP architecture maintains most of the benefits of custom asynchronous
design, whilst also providing programmability via conventional high-level languages.
Results show that the DRAP processor delivers considerably lower power
consumption when compared to a market-leading Very Long Instruction Word
(VLIW) processor and a low-power ARM processor. For example, DRAP resulted in
a reduction in power consumption of 20 times compared to the ARM7 processor, and
29 times compared to the TIC64x VLIW, when running the same benchmark capped
to the same throughput and for the same process technology (0.13μm). When
compared to an equivalent RICA design, DRAP was up to 22% larger than RICA but
resulted in a power reduction of up to 1.9 times. It was also capable of achieving up
to 2.8 times higher throughputs than RICA for the same benchmarks
Reconfigurable architectures for the next generation of mobile device telecommunications systems
Mobile devices have become a dominant tool in our daily lives. Business and
personal usage has escalated tremendously since the emergence of smartphones
and tablets. The combination of powerful processing in mobile devices, such as
smartphones and the Internet, have established a new era for communications
systems. This has put further pressure on the performance and efficiency of
telecommunications systems in delivering the aspirations of users. Mobile device
users no longer want devices that merely perform phone calls and messaging.
Rather, they look for further interactive applications such as video streaming,
navigation and real time social interaction. Such applications require a new set of
hardware and standards. The WiFi (IEEE 802.11) standard has been at the forefront
of reliable and high-speed internet access telecommunications. This is due to its
high signal quality (quality of service) and speed (throughput). However, its limited
availability and short range highlights the need for further protocols, in particular
when far away from access points or base stations. This led to the emergence of 3G
followed by 4G and the upcoming 5G standard that, if fully realised, will provide
another dimension in “anywhere, anytime internet connectivity.” On the other
hand, the WiMAX (IEEE 802.16) standard promises to exceed the WiFi signal
coverage range. The coverage range could be extended to kilometres at least with a
better or similar WiFi signal level.
This thesis considers a dynamically reconfigurable architecture that is capable of
processing various modules within telecommunications systems. Forward error
correction, coder and navigation modules are deployed in a unified low power
communication platform. These modules have been selected since they are among
those with the highest demand in terms of processing power, strict processing time
or throughput. The modules are mainly realised within WiFi and WiMAX systems
in addition to global positioning systems (GPS). The idea behind the selection of
these modules is to investigate the possibility of designing an architecture capable
of processing various systems and dynamically reconfiguring between them. The
GPS system is a power-hungry application and, at the same time, it is not needed
all of the time. Hence, one key idea presented in this thesis is to effectively exploit
the dynamic reconfiguration capability so as to reconfigure the architecture (GPS)
when it is not needed in order to process another needed application or function
such as WiFi or WiMAX. This will allow lower energy consumption and the
optimum usage of the hardware available on the device.
This work investigates the major current coarse-grain reconfigurable architectures.
A novel multi-rate convolution encoder is then designed and realised as a
reconfigurable fabric. This demonstrates the ability to adapt the algorithms
involved to meet various requirements. A throughput of between 200 and 800
Mbps has been achieved for the rates 1/2 to 7/8, which is a great achievement for
the proposed novel architecture. A reconfigurable interleaver is designed as a
standalone fabric and on a dynamically reconfigurable processor. High throughputs
exceeding 90 Mbps are achieved for the various supported block sizes. The Reed
Solomon coder is the next challenging system to be designed into a dynamically
reconfigurable processor. A novel Galois Field multiplier is designed and
integrated into the developed Reed Solomon reconfigurable processor. As a result
of this work, throughputs of 200Mbps and 93Mbps respectively for RS encoding
and decoding are achieved. A GPS correlation module is also investigated in this
work. This is the main part of the GPS receiver responsible for continuously
tracking GPS satellites and extracting messages from them. The challenging aspect
of this part is its real-time nature and the associated critical time constraints. This
work resulted in a novel dynamically reconfigurable multi-channel GPS correlator
with up to 72 simultaneous channels.
This work is a contribution towards a global unified processing platform that is
capable of processing communication-related operations efficiently and
dynamically with minimum energy consumption
Re-targetable tools and methodologies for the efficient deployment of high-level source code on coarse-grained dynamically reconfigurable architectures
Reconfigurable computing traditionally consists of a data path machine (such as an FPGA)
acting as a co-processor to a conventional microprocessor. This involves partitioning the application such that the data path intensive parts are implemented on the reconfigurable fabric, and
the control flow intensive parts are implemented on the microprocessor. Often the two parts
have to be written in different languages. New highly parallel data path architectures allow parallelism approaching that of FPGAs, but are able to be reconfigured very rapidly. As a result, it
is possible to use these architectures to perform control flow in a manner similar to a microprocessor, and thus a complete program can be described from an unmodified high-level language
(in particular C). This overcomes the historical instruction-level parallelism (ILP) wall.To make full use of the available parallelism , existing microprocessor tool flows are insufficient.
Data path machines are typically programmed via HDL tools from the ASIC design world.
This expresses algorithm s at a low er level than the application algorithm s are typically developed in. The work in this thesis builds upon earlier work to allow applications to be described
from high-level languages, by employing low-level optimisations in the compiler back-end and
working from the assembly, to maximise parallel efficiency. This consists of scheduling, where
known techniques are used to pack instructions into basic blocks that map well to the reconfigurable core (optimising spatial efficiency); then automatic pipelining is applied to dramatically
improve the achievable throughput (optimising temporal efficiency). Together these can be
thought of as “instruction-level parallelism done right”. Speed-ups of more than an order of
magnitude were achieved, yielding throughputs of 180-380M Pixels/s on typical image signal
processing tasks, matching the performance of hard-wired ASICs.Furthermore, conventional software-based simulation technologies for data path machines are
too slow for use in application verification. This thesis demonstrates how a high-speed software
emulator can be created for self-controlled dynamically reconfigurable data path machines,
using a static serialisation of the data paths in each configuration context. This yields run-time
performance several orders of magnitude higher than existing techniques, making it suitable for
use in feedback-directed optimisation