80 resultados para atom chip
Resumo:
Multiprocessor system-on-chip (MPSoC) designs utilize the available technology and communication architectures to meet the requirements of the upcoming applications. In MPSoC, the communication platform is both the key enabler, as well as the key differentiator for realizing efficient MPSoCs. It provides product differentiation to meet a diverse, multi-dimensional set of design constraints, including performance, power, energy, reconfigurability, scalability, cost, reliability and time-to-market. The communication resources of a single interconnection platform cannot be fully utilized by all kind of applications, such as the availability of higher communication bandwidth for computation but not data intensive applications is often unfeasible in the practical implementation. This thesis aims to perform the architecture-level design space exploration towards efficient and scalable resource utilization for MPSoC communication architecture. In order to meet the performance requirements within the design constraints, careful selection of MPSoC communication platform, resource aware partitioning and mapping of the application play important role. To enhance the utilization of communication resources, variety of techniques such as resource sharing, multicast to avoid re-transmission of identical data, and adaptive routing can be used. For implementation, these techniques should be customized according to the platform architecture. To address the resource utilization of MPSoC communication platforms, variety of architectures with different design parameters and performance levels, namely Segmented bus (SegBus), Network-on-Chip (NoC) and Three-Dimensional NoC (3D-NoC), are selected. Average packet latency and power consumption are the evaluation parameters for the proposed techniques. In conventional computing architectures, fault on a component makes the connected fault-free components inoperative. Resource sharing approach can utilize the fault-free components to retain the system performance by reducing the impact of faults. Design space exploration also guides to narrow down the selection of MPSoC architecture, which can meet the performance requirements with design constraints.
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Activated T helper (Th) cells have ability to differentiate into functionally distinct Th1, Th2 and Th17 subsets through a series of overlapping networks that include signaling and transcriptional control and the epigenetic mechanisms to direct immune responses. However, inappropriate execution in the differentiation process and abnormal function of these Th cells can lead to the development of several immune mediated diseases. Therefore, the thesis aimed at identifying genes and gene regulatory mechanisms responsible for Th17 differentiation and to study epigenetic changes associated with early stage of Th1/Th2 cell differentiation. Genome wide transcriptional profiling during early stages of human Th17 cell differentiation demonstrated differential regulation of several novel and currently known genes associated with Th17 differentiation. Selected candidate genes were further validated at protein level and their specificity for Th17 as compared to other T helper subsets was analyzed. Moreover, combination of RNA interference-mediated downregulation of gene expression, genome-wide transcriptome profiling and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq), combined with computational data integration lead to the identification of direct and indirect target genes of STAT3, which is a pivotal upstream transcription factor for Th17 cell polarization. Results indicated that STAT3 directly regulates the expression of several genes that are known to play a role in activation, differentiation, proliferation, and survival of Th17 cells. These results provide a basis for constructing a network regulating gene expression during early human Th17 differentiation. Th1 and Th2 lineage specific enhancers were identified from genome-wide maps of histone modifications generated from the cells differentiating towards Th1 and Th2 lineages at 72h. Further analysis of lineage-specific enhancers revealed known and novel transcription factors that potentially control lineage-specific gene expression. Finally, we found an overlap of a subset of enhancers with SNPs associated with autoimmune diseases through GWASs suggesting a potential role for enhancer elements in the disease development. In conclusion, the results obtained have extended our knowledge of Th differentiation and provided new mechanistic insights into dysregulation of Th cell differentiation in human immune mediated diseases.
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Advancements in IC processing technology has led to the innovation and growth happening in the consumer electronics sector and the evolution of the IT infrastructure supporting this exponential growth. One of the most difficult obstacles to this growth is the removal of large amount of heatgenerated by the processing and communicating nodes on the system. The scaling down of technology and the increase in power density is posing a direct and consequential effect on the rise in temperature. This has resulted in the increase in cooling budgets, and affects both the life-time reliability and performance of the system. Hence, reducing on-chip temperatures has become a major design concern for modern microprocessors. This dissertation addresses the thermal challenges at different levels for both 2D planer and 3D stacked systems. It proposes a self-timed thermal monitoring strategy based on the liberal use of on-chip thermal sensors. This makes use of noise variation tolerant and leakage current based thermal sensing for monitoring purposes. In order to study thermal management issues from early design stages, accurate thermal modeling and analysis at design time is essential. In this regard, spatial temperature profile of the global Cu nanowire for on-chip interconnects has been analyzed. It presents a 3D thermal model of a multicore system in order to investigate the effects of hotspots and the placement of silicon die layers, on the thermal performance of a modern ip-chip package. For a 3D stacked system, the primary design goal is to maximise the performance within the given power and thermal envelopes. Hence, a thermally efficient routing strategy for 3D NoC-Bus hybrid architectures has been proposed to mitigate on-chip temperatures by herding most of the switching activity to the die which is closer to heat sink. Finally, an exploration of various thermal-aware placement approaches for both the 2D and 3D stacked systems has been presented. Various thermal models have been developed and thermal control metrics have been extracted. An efficient thermal-aware application mapping algorithm for a 2D NoC has been presented. It has been shown that the proposed mapping algorithm reduces the effective area reeling under high temperatures when compared to the state of the art.
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Panel at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Heat shock factors (HSFs) are an evolutionarily well conserved family of transcription factors that coordinate stress-induced gene expression and direct versatile physiological processes in eukaryote organisms. The essentiality of HSFs for cellular homeostasis has been well demonstrated, mainly through HSF1-induced transcription of heat shock protein (HSP) genes. HSFs are important regulators of many fundamental processes such as gametogenesis, metabolic control and aging, and are involved in pathological conditions including cancer progression and neurodegenerative diseases. In each of the HSF-mediated processes, however, the detailed mechanisms of HSF family members and their complete set of target genes have remained unknown. Recently, rapid advances in chromatin studies have enabled genome-wide characterization of protein binding sites in a high resolution and in an unbiased manner. In this PhD thesis, these novel methods that base on chromatin immunoprecipitation (ChIP) are utilized and the genome-wide target loci for HSF1 and HSF2 are identified in cellular stress responses and in developmental processes. The thesis and its original publications characterize the individual and shared target genes of HSF1 and HSF2, describe HSF1 as a potent transactivator, and discover HSF2 as an epigenetic regulator that coordinates gene expression throughout the cell cycle progression. In male gametogenesis, novel physiological functions for HSF1 and HSF2 are revealed and HSFs are demonstrated to control the expression of X- and Y-chromosomal multicopy genes in a silenced chromatin environment. In stressed human cells, HSF1 and HSF2 are shown to coordinate the expression of a wide variety of genes including genes for chaperone machinery, ubiquitin, regulators of cell cycle progression and signaling. These results highlight the importance of cell type and cell cycle phase in transcriptional responses, reveal the myriad of processes that are adjusted in a stressed cell and describe novel mechanisms that maintain transcriptional memory in mitotic cell division.
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Nykyaikana yhteiskunta tavoittelee uusiutuvaa ja ympäristöä säästävää energiantuotantoa. Biopolttoaineiden käyttö vähentää fossiilisten polttoaineiden osuutta energiantuotannossa. Jotta biopolttoaineilla voidaan korvata fossiilisia polttoaineita, biopolttoaineita täytyy jalostaa. Tämän diplomityön tarkoituksena on selvittää puuhakkeen jalostuksen merkitystä hakkeen käytölle ja kannattavuudelle. Hakkeen kuivaamisella ja seulonnalla voidaan parantaa hakkeen käsittely- ja poltto-ominaisuuksia. Kosteuden ja tasalaatuisuuden merkitys suurenee, kun haketta käytetään pienissä kattiloissa. Pienissä kattiloissa lämmöntuotannon hyötysuhde pienenee merkittävästi kosteuden suurentuessa. Tällöin polttoaineen kulutus ja energiantuotantokustannukset suurenevat. Suuremmissa kattiloissa hyvälaatuisella hakkeella on mahdollista korvata kalliimpia vara- ja huippukuormapolttoaineita, kuten öljyä. Tällöin fossiilisten polttoaineiden osuus pienenee. Lisäksi kuivaaminen ja seulominen ovat edullisia jalostusprosesseja esimerkiksi pelletin tuotantoon verrattuna.
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The objective of this work was to study the effects of partial removal of wood hemicelluloses on the properties of kraft pulp.The work was conducted by extracting hemicelluloses (1) by a softwood chip pretreatment process prior to kraft pulping, (2) by alkaline extraction from bleached birch kraft pulp, and (3) by enzymatic treatment, xylanase treatment in particular, of bleached birch kraft pulp. The qualitative and quantitative changes in fibers and paper properties were evaluated. In addition, the applicability of the extraction concepts and hemicellulose-extracted birch kraft pulp as a raw material in papermaking was evaluated in a pilot-scale papermaking environment. The results showed that each examined hemicellulose extraction method has its characteristic effects on fiber properties, seen as differences in both the physical and chemical nature of the fibers. A prehydrolysis process prior to the kraft pulping process offered reductions in cooking time, bleaching chemical consumption and produced fibers with low hemicellulose content that are more susceptible to mechanically induced damages and dislocations. Softwood chip pretreatment for hemicellulose recovery prior to cooking, whether acidic or alkaline, had an impact on the physical properties of the non-refined and refined pulp. In addition, all the pretreated pulps exhibited slower beating response than the unhydrolyzed reference pulp. Both alkaline extraction and enzymatic (xylanase) treatment of bleached birch kraft pulp fibers indicated very selective hemicellulose removal, particularly xylan removal. Furthermore, these two hemicellulose-extracted birch kraft pulps were utilized in a pilot-scale papermaking environment in order to evaluate the upscalability of the extraction concepts. Investigations made using pilot paper machine trials revealed that some amount of alkalineextracted birch kraft pulp, with a 24.9% reduction in the total amount of xylan, could be used in the papermaking stock as a mixture with non-extracted pulp when producing 75 g/m2 paper. For xylanase-treated fibers there were no reductions in the mechanical properties of the 180 g/m2 paper produced compared to paper made from the control pulp, although there was a 14.2% reduction in the total amount of xylan in the xylanase-treated pulp compared to the control birch kraft pulp. This work emphasized the importance of the hemicellulose extraction method in providing new solutions to create functional fibers and in providing a valuable hemicellulose co-product stream. The hemicellulose removal concept therefore plays an important role in the integrated forest biorefinery scenario, where the target is to the co-production of hemicellulose-extracted pulp and hemicellulose-based chemicals or fuels.
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In this work, the feasibility of the floating-gate technology in analog computing platforms in a scaled down general-purpose CMOS technology is considered. When the technology is scaled down the performance of analog circuits tends to get worse because the process parameters are optimized for digital transistors and the scaling involves the reduction of supply voltages. Generally, the challenge in analog circuit design is that all salient design metrics such as power, area, bandwidth and accuracy are interrelated. Furthermore, poor flexibility, i.e. lack of reconfigurability, the reuse of IP etc., can be considered the most severe weakness of analog hardware. On this account, digital calibration schemes are often required for improved performance or yield enhancement, whereas high flexibility/reconfigurability can not be easily achieved. Here, it is discussed whether it is possible to work around these obstacles by using floating-gate transistors (FGTs), and analyze problems associated with the practical implementation. FGT technology is attractive because it is electrically programmable and also features a charge-based built-in non-volatile memory. Apart from being ideal for canceling the circuit non-idealities due to process variations, the FGTs can also be used as computational or adaptive elements in analog circuits. The nominal gate oxide thickness in the deep sub-micron (DSM) processes is too thin to support robust charge retention and consequently the FGT becomes leaky. In principle, non-leaky FGTs can be implemented in a scaled down process without any special masks by using “double”-oxide transistors intended for providing devices that operate with higher supply voltages than general purpose devices. However, in practice the technology scaling poses several challenges which are addressed in this thesis. To provide a sufficiently wide-ranging survey, six prototype chips with varying complexity were implemented in four different DSM process nodes and investigated from this perspective. The focus is on non-leaky FGTs, but the presented autozeroing floating-gate amplifier (AFGA) demonstrates that leaky FGTs may also find a use. The simplest test structures contain only a few transistors, whereas the most complex experimental chip is an implementation of a spiking neural network (SNN) which comprises thousands of active and passive devices. More precisely, it is a fully connected (256 FGT synapses) two-layer spiking neural network (SNN), where the adaptive properties of FGT are taken advantage of. A compact realization of Spike Timing Dependent Plasticity (STDP) within the SNN is one of the key contributions of this thesis. Finally, the considerations in this thesis extend beyond CMOS to emerging nanodevices. To this end, one promising emerging nanoscale circuit element - memristor - is reviewed and its applicability for analog processing is considered. Furthermore, it is discussed how the FGT technology can be used to prototype computation paradigms compatible with these emerging two-terminal nanoscale devices in a mature and widely available CMOS technology.
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Graphene is a material with extraordinary properties. Its mechanical and electrical properties are unparalleled but the difficulties in its production are hindering its breakthrough in on applications. Graphene is a two-dimensional material made entirely of carbon atoms and it is only a single atom thick. In this work, properties of graphene and graphene based materials are described, together with their common preparation techniques and related challenges. This Thesis concentrates on the topdown techniques, in which natural graphite is used as a precursor for the graphene production. Graphite consists of graphene sheets, which are stacked together tightly. In the top-down techniques various physical or chemical routes are used to overcome the forces keeping the graphene sheets together, and many of them are described in the Thesis. The most common chemical method is the oxidisation of graphite with strong oxidants, which creates a water-soluble graphene oxide. The properties of graphene oxide differ significantly from pristine graphene and, therefore, graphene oxide is often reduced to form materials collectively known as reduced graphene oxide. In the experimental part, the main focus is on the chemical and electrochemical reduction of graphene oxide. A novel chemical route using vanadium is introduced and compared to other common chemical graphene oxide reduction methods. A strong emphasis is placed on electrochemical reduction of graphene oxide in various solvents. Raman and infrared spectroscopy are both used in in situ spectroelectrochemistry to closely monitor the spectral changes during the reduction process. These in situ techniques allow the precise control over the reduction process and even small changes in the material can be detected. Graphene and few layer graphene were also prepared using a physical force to separate these materials from graphite. Special adsorbate molecules in aqueous solutions, together with sonic treatment, produce stable dispersions of graphene and few layer graphene sheets in water. This mechanical exfoliation method damages the graphene sheets considerable less than the chemical methods, although it suffers from a lower yield.
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This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.
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The Large Hadron Collider (LHC) in The European Organization for Nuclear Research (CERN) will have a Long Shutdown sometime during 2017 or 2018. During this time there will be maintenance and a possibility to install new detectors. After the shutdown the LHC will have a higher luminosity. A promising new type of detector for this high luminosity phase is a Triple-GEM detector. During the shutdown these detectors will be installed at the Compact Muon Solenoid (CMS) experiment. The Triple-GEM detectors are now being developed at CERN and alongside also a readout ASIC chip for the detector. In this thesis a simulation model was developed for the ASICs analog front end. The model will help to carry out more extensive simulations and also simulate the whole chip before the whole design is finished. The proper functioning of the model was tested with simulations, which are also presented in the thesis.
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Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented
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Työssä tutkittiin polttoaineterminaalissa varastoitavan puupolttoaineen laadunmuutoksia. Tutkimuksessa tarkasteltiin hakettamattomien rankapuiden ja rankapuuhakkeen kosteuden ja lämpöarvon muutosta. Myös kuiva-ainetappiota tutkittiin aikaisempien tutkimusten perusteella. Tutkimusaineisto kerättiin Etelä-Savon Energian polttoaineterminaaleista. Kosteus-pitoisuuksia mitattiin Hydromette M2050 -pikakosteusmittarilla ja uunikuivaus-menetelmällä standardin SFS-EN 14774 mukaisesti. Tutkimuksessa huomattiin pikakosteusmittarin toimivan riittävän luotettavalla tasolla rankapuiden mittauksissa, mutta hakkeen mittauksissa mittari osoittautui toimimattomaksi. Varastointiaika ei vaikuttanut polttoaineiden lämpöarvoihin, mutta kosteuspitoisuus vaihteli suuresti. Tutkimustuloksista pääteltiin rangan kuivuvan terminaalivarastossa ja hakkeen kosteuden pysyvän vakiona. Energiasisällön puolesta rankapuuta voidaan varastoida yli 2 vuotta, mutta hakkeen varastointiaika tulisi pitää mahdollisimman lyhyenä.
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Due to various advantages such as flexibility, scalability and updatability, software intensive systems are increasingly embedded in everyday life. The constantly growing number of functions executed by these systems requires a high level of performance from the underlying platform. The main approach to incrementing performance has been the increase of operating frequency of a chip. However, this has led to the problem of power dissipation, which has shifted the focus of research to parallel and distributed computing. Parallel many-core platforms can provide the required level of computational power along with low power consumption. On the one hand, this enables parallel execution of highly intensive applications. With their computational power, these platforms are likely to be used in various application domains: from home use electronics (e.g., video processing) to complex critical control systems. On the other hand, the utilization of the resources has to be efficient in terms of performance and power consumption. However, the high level of on-chip integration results in the increase of the probability of various faults and creation of hotspots leading to thermal problems. Additionally, radiation, which is frequent in space but becomes an issue also at the ground level, can cause transient faults. This can eventually induce a faulty execution of applications. Therefore, it is crucial to develop methods that enable efficient as well as resilient execution of applications. The main objective of the thesis is to propose an approach to design agentbased systems for many-core platforms in a rigorous manner. When designing such a system, we explore and integrate various dynamic reconfiguration mechanisms into agents functionality. The use of these mechanisms enhances resilience of the underlying platform whilst maintaining performance at an acceptable level. The design of the system proceeds according to a formal refinement approach which allows us to ensure correct behaviour of the system with respect to postulated properties. To enable analysis of the proposed system in terms of area overhead as well as performance, we explore an approach, where the developed rigorous models are transformed into a high-level implementation language. Specifically, we investigate methods for deriving fault-free implementations from these models into, e.g., a hardware description language, namely VHDL.
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The original contribution of this thesis to knowledge are novel digital readout architectures for hybrid pixel readout chips. The thesis presents asynchronous bus-based architecture, a data-node based column architecture and a network-based pixel matrix architecture for data transportation. It is shown that the data-node architecture achieves readout efficiency 99% with half the output rate as a bus-based system. The network-based solution avoids “broken” columns due to some manufacturing errors, and it distributes internal data traffic more evenly across the pixel matrix than column-based architectures. An improvement of > 10% to the efficiency is achieved with uniform and non-uniform hit occupancies. Architectural design has been done using transaction level modeling (TLM) and sequential high-level design techniques for reducing the design and simulation time. It has been possible to simulate tens of column and full chip architectures using the high-level techniques. A decrease of > 10 in run-time is observed using these techniques compared to register transfer level (RTL) design technique. Reduction of 50% for lines-of-code (LoC) for the high-level models compared to the RTL description has been achieved. Two architectures are then demonstrated in two hybrid pixel readout chips. The first chip, Timepix3 has been designed for the Medipix3 collaboration. According to the measurements, it consumes < 1 W/cm^2. It also delivers up to 40 Mhits/s/cm^2 with 10-bit time-over-threshold (ToT) and 18-bit time-of-arrival (ToA) of 1.5625 ns. The chip uses a token-arbitrated, asynchronous two-phase handshake column bus for internal data transfer. It has also been successfully used in a multi-chip particle tracking telescope. The second chip, VeloPix, is a readout chip being designed for the upgrade of Vertex Locator (VELO) of the LHCb experiment at CERN. Based on the simulations, it consumes < 1.5 W/cm^2 while delivering up to 320 Mpackets/s/cm^2, each packet containing up to 8 pixels. VeloPix uses a node-based data fabric for achieving throughput of 13.3 Mpackets/s from the column to the EoC. By combining Monte Carlo physics data with high-level simulations, it has been demonstrated that the architecture meets requirements of the VELO (260 Mpackets/s/cm^2 with efficiency of 99%).