19 research outputs found
Improving Energy Efficiency of OFDM Using Adaptive Precision Reconfigurable FFT
International audienceBeing an essential issue in digital systems, especially battery-powered devices, energy efficiency has been the subject of intensive research. In this research, a multi-precision FFT module with dynamic run-time reconfigurability is proposed to trade off accuracy with the energy efficiency of OFDM in an SDR-based architecture. To support variable-size FFT, a reconfigurable memory-based architecture is investigated. It is revealed that the radix-4 FFT has the minimum computational complexity in this architecture. Regarding implementation constraints such as fixed-width memory, a noise model is exploited to statistically analyze the proposed architecture. The required FFT word-lengths for different criteria—namely BER, modulation scheme, FFT size, and SNR—are computed analytically and confirmed by simulations in AWGN and Rayleigh fading channels. At run-time, the most energy-efficient word-length is chosen and the FFT is reconfigured until the required application-specific BER is met. Evaluations show that the implementation area and the number of memory accesses are reduced. The results obtained from synthesizing basic operators of the proposed design on an FPGA show energy consumption experienced a saving of over 80 %
Generic low power reconfigurable distributed arithmetic processor
Higher performance, lower cost, increasingly minimizing integrated circuit components, and
higher packaging density of chips are ongoing goals of the microelectronic and computer
industry. As these goals are being achieved, however, power consumption and flexibility are
increasingly becoming bottlenecks that need to be addressed with the new technology in Very
Large-Scale Integrated (VLSI) design.
For modern systems, more energy is required to support the powerful computational capability
which accords with the increasing requirements, and these requirements cause the change of
standards not only in audio and video broadcasting but also in communication such as wireless
connection and network protocols. Powerful flexibility and low consumption are repellent, but
their combination in one system is the ultimate goal of designers.
A generic domain-specific low-power reconfigurable processor for the distributed
arithmetic algorithm is presented in this dissertation. This domain reconfigurable processor
features high efficiency in terms of area, power and delay, which approaches the
performance of an ASIC design, while retaining the flexibility of programmable platforms.
The architecture not only supports typical distributed arithmetic algorithms which can be
found in most still picture compression standards and video conferencing standards, but
also offers implementation ability for other distributed arithmetic algorithms found in
digital signal processing, telecommunication protocols and automatic control.
In this processor, a simple reconfigurable low power control unit is implemented with
good performance in area, power and timing. The generic characteristic of the architecture
makes it applicable for any small and medium size finite state machines which can be used
as control units to implement complex system behaviour and can be found in almost all
engineering disciplines. Furthermore, to map target applications efficiently onto the
proposed architecture, a new algorithm is introduced for searching for the best common
sharing terms set and it keeps the area and power consumption of the implementation at
low level. The software implementation of this algorithm is presented, which can be used
not only for the proposed architecture in this dissertation but also for all the
implementations with adder-based distributed arithmetic algorithms. In addition, some low
power design techniques are applied in the architecture, such as unsymmetrical design
style including unsymmetrical interconnection arranging, unsymmetrical PTBs selection
and unsymmetrical mapping basic computing units. All these design techniques achieve
extraordinary power consumption saving. It is believed that they can be extended to more
low power designs and architectures.
The processor presented in this dissertation can be used to implement complex, high
performance distributed arithmetic algorithms for communication and image processing
applications with low cost in area and power compared with the traditional
methods
The JM-Filter to detect specific frequency in monitored signal
The Discrete Fourier Transform (DFT) is a mathematical procedure that stands at the center of the processing inside a digital signal processor. It has been widely known and argued in relevant literature that the Fast Fourier Transform (FFT) is useless in detecting specific frequencies in a monitored signal of length N because most of the computed results are ignored. In this paper, we present an efficient FFT-based method to detect specific frequencies in a monitored signal, which will then be compared to the most frequently used method which is the recursive Goertzel algorithm that detects and analyses one selectable frequency component from a discrete signal. The proposed JM-Filter algorithm presents a reduction of iterations compared to the first and second order Goertzel algorithm by a factor of r, where r represents the radix of the JM-Filter. The obtained results are significant in terms of computational reduction and accuracy in fixed-point implementation. Gains of 15 dB and 19 dB in signal to quantization noise ratio (SQNR) were respectively observed for the proposed first and second order radix-8 JM-Filter in comparison to Goertzel algorithm
Adaptive Baseband Pro cessing and Configurable Hardware for Wireless Communication
The world of information is literally at one’s fingertips, allowing access to previously unimaginable amounts of data, thanks to advances in wireless communication. The growing demand for high speed data has necessitated theuse of wider bandwidths, and wireless technologies such as Multiple-InputMultiple-Output (MIMO) have been adopted to increase spectral efficiency.These advanced communication technologies require sophisticated signal processing, often leading to higher power consumption and reduced battery life.Therefore, increasing energy efficiency of baseband hardware for MIMO signal processing has become extremely vital. High Quality of Service (QoS)requirements invariably lead to a larger number of computations and a higherpower dissipation. However, recognizing the dynamic nature of the wirelesscommunication medium in which only some channel scenarios require complexsignal processing, and that not all situations call for high data rates, allowsthe use of an adaptive channel aware signal processing strategy to provide adesired QoS. Information such as interference conditions, coherence bandwidthand Signal to Noise Ratio (SNR) can be used to reduce algorithmic computations in favorable channels. Hardware circuits which run these algorithmsneed flexibility and easy reconfigurability to switch between multiple designsfor different parameters. These parameters can be used to tune the operations of different components in a receiver based on feedback from the digitalbaseband. This dissertation focuses on the optimization of digital basebandcircuitry of receivers which use feedback to trade power and performance. Aco-optimization approach, where designs are optimized starting from the algorithmic stage through the hardware architectural stage to the final circuitimplementation is adopted to realize energy efficient digital baseband hardwarefor mobile 4G devices. These concepts are also extended to the next generation5G systems where the energy efficiency of the base station is improved.This work includes six papers that examine digital circuits in MIMO wireless receivers. Several key blocks in these receiver include analog circuits thathave residual non-linearities, leading to signal intermodulation and distortion.Paper-I introduces a digital technique to detect such non-linearities and calibrate analog circuits to improve signal quality. The concept of a digital nonlinearity tuning system developed in Paper-I is implemented and demonstratedin hardware. The performance of this implementation is tested with an analogchannel select filter, and results are presented in Paper-II. MIMO systems suchas the ones used in 4G, may employ QR Decomposition (QRD) processors tosimplify the implementation of tree search based signal detectors. However,the small form factor of the mobile device increases spatial correlation, whichis detrimental to signal multiplexing. Consequently, a QRD processor capableof handling high spatial correlation is presented in Paper-III. The algorithm and hardware implementation are optimized for carrier aggregation, which increases requirements on signal processing throughput, leading to higher powerdissipation. Paper-IV presents a method to perform channel-aware processingwith a simple interpolation strategy to adaptively reduce QRD computationcount. Channel properties such as coherence bandwidth and SNR are used toreduce multiplications by 40% to 80%. These concepts are extended to usetime domain correlation properties, and a full QRD processor for 4G systemsfabricated in 28 nm FD-SOI technology is presented in Paper-V. The designis implemented with a configurable architecture and measurements show thatcircuit tuning results in a highly energy efficient processor, requiring 0.2 nJ to1.3 nJ for each QRD. Finally, these adaptive channel-aware signal processingconcepts are examined in the scope of the next generation of communicationsystems. Massive MIMO systems increase spectral efficiency by using a largenumber of antennas at the base station. Consequently, the signal processingat the base station has a high computational count. Paper-VI presents a configurable detection scheme which reduces this complexity by using techniquessuch as selective user detection and interpolation based signal processing. Hardware is optimized for resource sharing, resulting in a highly reconfigurable andenergy efficient uplink signal detector
Interconnect architectures for dynamically partially reconfigurable systems
Dynamically partially reconfigurable FPGAs (Field-Programmable Gate Arrays) allow
hardware modules to be placed and removed at runtime while other parts of the system
keep working. With their potential benefits, they have been the topic of a great
deal of research over the last decade. To exploit the partial reconfiguration capability of
FPGAs, there is a need for efficient, dynamically adaptive communication infrastructure
that automatically adapts as modules are added to and removed from the system.
Many bus and network-on-chip (NoC) architectures have been proposed to exploit this
capability on FPGA technology. However, few realizations have been reported in the
public literature to demonstrate or compare their performance in real world applications.
While partial reconfiguration can offer many benefits, it is still rarely exploited in practical
applications. Few full realizations of partially reconfigurable systems in current
FPGA technologies have been published. More application experiments are required to
understand the benefits and limitations of implementing partially reconfigurable systems
and to guide their further development. The motivation of this thesis is to fill this
research gap by providing empirical evidence of the cost and benefits of different interconnect
architectures. The results will provide a baseline for future research and will
be directly useful for circuit designers who must make a well-reasoned choice between
the alternatives.
This thesis contains the results of experiments to compare different NoC and bus interconnect
architectures for FPGA-based designs in general and dynamically partially
reconfigurable systems. These two interconnect schemes are implemented and evaluated
in terms of performance, area and power consumption using FFT (Fast Fourier
Transform) andANN(Artificial Neural Network) systems as benchmarks. Conclusions
drawn from these results include recommendations concerning the interconnect approach
for different kinds of applications. It is found that a NoC provides much better
performance than a single channel bus and similar performance to a multi-channel bus
in both parallel and parallel-pipelined FFT systems. This suggests that a NoC is a better choice for systems with multiple simultaneous communications like the FFT. Bus-based
interconnect achieves better performance and consume less area and power than NoCbased
scheme for the fully-connected feed-forward NN system. This suggests buses
are a better choice for systems that do not require many simultaneous communications
or systems with broadcast communications like a fully-connected feed-forward NN.
Results from the experiments with dynamic partial reconfiguration demonstrate that
buses have the advantages of better resource utilization and smaller reconfiguration
time and memory than NoCs. However, NoCs are more flexible and expansible. They
have the advantage of placing almost all of the communication infrastructure in the
dynamic reconfiguration region. This means that different applications running on the
FPGA can use different interconnection strategies without the overhead of fixed bus
resources in the static region.
Another objective of the research is to examine the partial reconfiguration process and
reconfiguration overhead with current FPGA technologies. Partial reconfiguration allows
users to efficiently change the number of running PEs to choose an optimal powerperformance
operating point at the minimum cost of reconfiguration. However, this
brings drawbacks including resource utilization inefficiency, power consumption overhead
and decrease in system operating frequency. The experimental results report a
50% of resource utilization inefficiency with a power consumption overhead of less
than 5% and a decrease in frequency of up to 32% compared to a static implementation.
The results also show that most of the drawbacks of partial reconfiguration implementation
come from the restrictions and limitations of partial reconfiguration design flow.
If these limitations can be addressed, partial reconfiguration should still be considered
with its potential benefits.Thesis (Ph.D.) -- University of Adelaide, School of Electrical and Electronic Engineering, 201
Fast Fourier transforms on energy-efficient application-specific processors
Many of the current applications used in battery powered devices are from digital signal processing, telecommunication, and multimedia domains. Traditionally application-specific fixed-function circuits have been used in these designs in form of application-specific integrated circuits (ASIC) to reach the required performance and energy-efficiency. The complexity of these applications has increased over the years, thus the design complexity has increased even faster, which implies increased design time. At the same time, there are more and more standards to be supported, thus using optimised fixed-function implementations for all the functions in all the standards is impractical. The non-recurring engineering costs for integrated circuits have also increased significantly, so manufacturers can only afford fewer chip iterations. Although tailoring the circuit for a specific application provides the best performance and/or energy-efficiency, such approach lacks flexibility. E.g., if an error is found after the manufacturing, an expensive chip iteration is required. In addition, new functionalities cannot be added afterwards to support evolution of standards.
Flexibility can be obtained with software based implementation technologies. Unfortunately, general-purpose processors do not provide the energy-efficiency of the fixed-function circuit designs. A useful trade-off between flexibility and performance is implementation based on application-specific processors (ASP) where programmability provides the flexibility and computational resources customised for the given application provide the performance.
In this Thesis, application-specific processors are considered by using fast Fourier transform as the representative algorithm. The architectural template used here is transport triggered architecture (TTA) which resembles very long instruction word machines but the operand execution resembles data flow machines rather than traditional operand triggering. The developed TTA processors exploit inherent parallelism of the application. In addition, several characteristics of the application have been identified and those are exploited by developing customised functional units for speeding up the execution. Several customisations are proposed for the data path of the processor but it is also important to match the memory bandwidth to the computation speed. This calls for a memory organisation supporting parallel memory accesses. The proposed optimisations have been used to improve the energy-efficiency of the processor and experiments show that a programmable solution can have energy-efficiency comparable to fixed-function ASIC designs
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Photonic Interconnects Beyond High Bandwidth
The extraordinary growth of parallelism in high-performance computing requires efficient data communication for scaling compute performance. High-performance computing systems have been using photonic links for communication of large bandwidth-distance product during the last decade. Photonic interconnection networks, however, should not be a wire-for-wire replacement based on conventional electrical counterparts. Features of photonics beyond high bandwidth, such as transparent bandwidth steering, can implement important functionalities needed by applications. In another aspect, application characteristics can be exploited to design better photonic interconnects. Therefore, this thesis explores codesign opportunities at the intersection between photonic interconnect architectures and high-performance computing applications. The key accomplishments of this thesis, ranging from system level to node level, are as follows.
Chapter 2 presents a system-level architecture that leverages photonic switching to enable a reconfigurable interconnect. The architecture, called Flexfly, reconfigures the inter-group level of the widely-used Dragonfly topology using information about the application’s communication pattern. It can steal additional direct bandwidth for communication-intensive group pairs. Simulations with applications such as GTC, Nekbone and LULESH show up to 1.8x speedup over Dragonfly paired with UGAL routing, along with halved hop count and latency for cross-group messages. To demonstrate the effectiveness of our approach, we built a 32-node Flexfly prototype using a silicon photonic switch connecting four groups and demonstrated 820 ns interconnect reconfiguration time. This is the first demonstration of silicon photonic switching and bandwidth steering in a high-performance computing cluster.
Chapter 3 extends photonic switching to the node level and presents a reconfigurable silicon photonic memory interconnect for many-core architectures. The interconnect targets at important memory access issues, such as network-on-chip hot-spots and non-uniform memory access. Integrated with the processor through 2.5D/3D stacking, a fast-tunable silicon photonic memory tunnel can transparently direct traffic from any off-chip memory to any on-chip interface – thus alleviating the hot-spot and non-uniform access effects. We demonstrated the operation of our proposed architecture using a tunable laser, a 4-port silicon photonic switch (four wavelength-routed memory channels) and a 4x4 mesh network-on-chip synthesized by FPGA. The emulated system achieves a 15-ns channel switching time. Simulations based on a 12-core 4-memory model show that for such switching speeds the interconnect system can realize a 2x speedup for the STREAM benchmark in the hot-spot scenario and a reduction of execution time for data-intensive applications such as 3D stencil and K-means clustering by 23% and 17%, respectively.
Chapters 4 explores application-level characteristics that can be exploited to hide photonic path setup delays. In view of the frequent reuse of optical circuits by many applications, we proposed a circuit-cached scheme that amortizes the setup overhead by maximizing circuit reuses. In order to improve circuit “hit” rates, we developed a reuse-distance based replacement policy called “Farthest Next Use”. We further investigated the tradeoffs between the realized hit rate and energy consumption. Finally, we experimentally demonstrated the feasibility of the proposed concept using silicon photonic devices in an FPGA-controlled network testbed.
Chapter 5 proceeds to develop an application-guided circuit-prefetch scheme. By learning temporal locality and communication patterns from upper-layer applications, the scheme not only caches a set of circuits for reuses, but also proactively prefetches circuits based on predictions. We applied this technique to communication patterns from a spectrum of science and engineering applications. The results show that setup delays via circuit misses are significantly reduced, showing how the proposed technique can improve circuit switching in photonic interconnects