Providing support for multimedia applications on low-power mobile devices
remains a significant research challenge. This is primarily due to two reasons:
• Portable mobile devices have modest sizes and weights, and therefore
inadequate resources, low CPU processing power, reduced display capabilities,
limited memory and battery lifetimes as compared to desktop
and laptop systems.
• On the other hand, multimedia applications tend to have distinctive QoS
and processing requirementswhichmake themextremely resource-demanding.
This innate conflict introduces key research challenges in the design of multimedia
applications and device-level power optimization.
Energy efficiency in this kind of platforms can be achieved only via a synergistic
hardware and software approach. In fact, while System-on-Chips are
more and more programmable thus providing functional flexibility, hardwareonly
power reduction techniques cannot maintain consumption under acceptable
bounds.
It is well understood both in research and industry that system configuration
andmanagement cannot be controlled efficiently only relying on low-level
firmware and hardware drivers. In fact, at this level there is lack of information
about user application activity and consequently about the impact of power
management decision on QoS.
Even though operating system support and integration is a requirement
for effective performance and energy management, more effective and QoSsensitive
power management is possible if power awareness and hardware
configuration control strategies are tightly integratedwith domain-specificmiddleware
services.
The main objective of this PhD research has been the exploration and the
integration of amiddleware-centric energymanagement with applications and
operating-system. We choose to focus on the CPU-memory and the video subsystems,
since they are the most power-hungry components of an embedded
system. A second main objective has been the definition and implementation
of software facilities (like toolkits, API, and run-time engines) in order to improve
programmability and performance efficiency of such platforms.
Enhancing energy efficiency and programmability ofmodernMulti-Processor
System-on-Chips (MPSoCs)
Consumer applications are characterized by tight time-to-market constraints
and extreme cost sensitivity. The software that runs on modern embedded
systems must be high performance, real time, and even more important low
power. Although much progress has been made on these problems, much
remains to be done.
Multi-processor System-on-Chip (MPSoC) are increasingly popular platforms
for high performance embedded applications. This leads to interesting
challenges in software development since efficient software development is a
major issue for MPSoc designers.
An important step in deploying applications on multiprocessors is to allocate
and schedule concurrent tasks to the processing and communication resources
of the platform. The problem of allocating and scheduling precedenceconstrained
tasks on processors in a distributed real-time system is NP-hard.
There is a clear need for deployment technology that addresses thesemulti processing
issues. This problem can be tackled by means of specific middleware
which takes care of allocating and scheduling tasks on the different processing
elements and which tries also to optimize the power consumption of the entire
multiprocessor platform.
This dissertation is an attempt to develop insight into efficient, flexible and
optimalmethods for allocating and scheduling concurrent applications tomultiprocessor
architectures.
It is a well-known problem in literature: this kind of optimization problems
are very complex even in much simplified variants, therefore most authors
propose simplified models and heuristic approaches to solve it in reasonable
time. Model simplification is often achieved by abstracting away platform
implementation ”details”. As a result, optimization problems become more
tractable, even reaching polynomial time complexity. Unfortunately, this approach
creates an abstraction gap between the optimization model and the real
HW-SW platform. The main issue with heuristic or, more in general, with incomplete
search is that they introduce an optimality gap of unknown size. They
provide very limited or no information on the distance between the best computed
solution and the optimal one.
The goal of this work is to address both abstraction and optimality gaps,
formulating accurate models which accounts for a number of ”non-idealities”
in real-life hardware platforms, developing novel mapping algorithms that deterministically
find optimal solutions, and implementing software infrastructures
required by developers to deploy applications for the targetMPSoC platforms.
Energy Efficient LCDBacklightAutoregulation on Real-LifeMultimediaAp-
plication Processor
Despite the ever increasing advances in Liquid Crystal Display’s (LCD) technology,
their power consumption is still one of the major limitations to the battery
life of mobile appliances such as smart phones, portable media players,
gaming and navigation devices. There is a clear trend towards the increase of
LCD size to exploit the multimedia capabilities of portable devices that can receive
and render high definition video and pictures. Multimedia applications
running on these devices require LCD screen sizes of 2.2 to 3.5 inches andmore
to display video sequences and pictures with the required quality.
LCD power consumption is dependent on the backlight and pixel matrix
driving circuits and is typically proportional to the panel area. As a result, the
contribution is also likely to be considerable in future mobile appliances. To
address this issue, companies are proposing low power technologies suitable
for mobile applications supporting low power states and image control techniques.
On the research side, several power saving schemes and algorithms can be
found in literature. Some of them exploit software-only techniques to change
the image content to reduce the power associated with the crystal polarization,
some others are aimed at decreasing the backlight level while compensating
the luminance reduction by compensating the user perceived quality degradation
using pixel-by-pixel image processing algorithms. The major limitation of
these techniques is that they rely on the CPU to perform pixel-based manipulations
and their impact on CPU utilization and power consumption has not
been assessed.
This PhDdissertation shows an alternative approach that exploits in a smart
and efficient way the hardware image processing unit almost integrated in every
current multimedia application processors to implement a hardware assisted
image compensation that allows dynamic scaling of the backlight with
a negligible impact on QoS. The proposed approach overcomes CPU-intensive
techniques by saving system power without requiring either a dedicated display technology or hardware modification.
Thesis Overview
The remainder of the thesis is organized as follows.
The first part is focused on enhancing energy efficiency and programmability
of modern Multi-Processor System-on-Chips (MPSoCs). Chapter 2 gives
an overview about architectural trends in embedded systems, illustrating the
principal features of new technologies and the key challenges still open. Chapter
3 presents a QoS-driven methodology for optimal allocation and frequency
selection for MPSoCs. The methodology is based on functional simulation
and full system power estimation. Chapter 4 targets allocation and scheduling
of pipelined stream-oriented applications on top of distributed memory
architectures with messaging support. We tackled the complexity of the problem
by means of decomposition and no-good generation, and prove the increased
computational efficiency of this approach with respect to traditional
ones. Chapter 5 presents a cooperative framework to solve the allocation,
scheduling and voltage/frequency selection problem to optimality for energyefficient
MPSoCs, while in Chapter 6 applications with conditional task graph
are taken into account. Finally Chapter 7 proposes a complete framework,
called Cellflow, to help programmers in efficient software implementation on
a real architecture, the Cell Broadband Engine processor.
The second part is focused on energy efficient software techniques for LCD
displays. Chapter 8 gives an overview about portable device display technologies,
illustrating the principal features of LCD video systems and the key challenges
still open. Chapter 9 shows several energy efficient software techniques
present in literature, while Chapter 10 illustrates in details our method for saving
significant power in an LCD panel.
Finally, conclusions are drawn, reporting the main research contributions
that have been discussed throughout this dissertation.
| Identifer | oai:union.ndltd.org:unibo.it/oai:amsdottorato.cib.unibo.it:921 |
| Date | 17 April 2008 |
| Creators | Ruggiero, Martino <1979> |
| Contributors | Benini, Luca |
| Publisher | Alma Mater Studiorum - Università di Bologna |
| Source Sets | Università di Bologna |
| Language | English |
| Detected Language | English |
| Type | Doctoral Thesis, PeerReviewed |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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