The global energy crisis and environmental concerns (e.g. global warming) have driven the IT community into the green computing era. Of clean, renewable energy sources, solar power is the most promising. While efforts...
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The global energy crisis and environmental concerns (e.g. global warming) have driven the IT community into the green computing era. Of clean, renewable energy sources, solar power is the most promising. While efforts have been made to improve the performance-per-watt, conventional architecture power management schemes incur significant solar energy loss since they are largely workload-driven and unaware of the supply-side attributes. Existing solar power harvesting techniques improve the energy utilization but increase the environmental burden and capital investment due to the inclusion of large-scale batteries. Moreover, solar power harvesting itself cannot guarantee high performance without appropriate load adaptation. To this end, we propose SolarCore, a solar energy driven, multi-core architecture power management scheme that combines maximal power provisioning control and workload run-time optimization. Using real-world meteorological data across different geographic sites and seasons, we show that SolarCore is capable of achieving the optimal operation condition (e.g. maximal power point) of solar panels autonomously under various environmental conditions with a high green energy utilization of 82% on average. We propose efficient heuristics for allocating the time varying solar power across multiple cores and our algorithm can further improve the workload performance by 10.8% compared with that of round-robin adaptation, and at least 43% compared with that of conventional fixed-power budget control. This paper makes the first step on maximally reducing the carbon footprint of computing systems through the usage of renewable energy sources. We expect that the novel joint optimization techniques proposed in this paper will contribute to building a truly sustainable, high-performance computing environment.
Phase Change Memory (PCM) is one of the most promising technologies among emerging non-volatile memories. PCM stores data in crystalline and amorphous phases of the GST material using large differences in their electr...
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Phase Change Memory (PCM) is one of the most promising technologies among emerging non-volatile memories. PCM stores data in crystalline and amorphous phases of the GST material using large differences in their electrical resistivity. Although it is possible to design a high capacity memory system by storing multiple bits at intermediate levels between the highest and lowest resistance states of PCM, it is difficult to obtain the tight distribution required for accurate reading of the data. Moreover, the required programming latency and energy for a Multiple Level PCM (MLC-PCM) cell is not trivial and can act as a major hurdle in adopting multilevel PCM in a high-density memory architecture design. Furthermore, the effect of process variation (PV) on PCM cell exacerbates the variability in necessary programming current and hence the target resistance spread, leading to the demand for high-latency, multi-iteration-based programming-and-verify write schemes for MLC-PCM. PV-aware control of programming current, programming using staircase down current pulses and programming using increasing reset current pulses are some of the traditional techniques used to achieve optimum programming energy, write latency and accuracy, but they usually target on optimizing only one aspect of the design. In this paper, we address the high-write latency and process variation issues of MLC-PCM by introducing Mercury: A fast and energy efficient multi-level cell based phase change memory architecture. Mercury adapts the programming scheme of a multi-level PCM cell by taking into consideration the initial state of the cell, the target resistance to be programmed and the effect of process variation on the programming current profile of the cell. The proposed techniques act at circuit as well as microarchitecture levels. Simulation results show that Mercury achieves 10% saving in programming latency and 25% saving in programming energy for the PCM memory system compared to that of the tradit
Multiple-input multiple-output (MIMO) systems can be observed in a huge variety of transmission links and network parts and have attracted a lot of attention since the mid 90's. In the field of optical MIMO transm...
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Multiple-input multiple-output (MIMO) systems can be observed in a huge variety of transmission links and network parts and have attracted a lot of attention since the mid 90's. In the field of optical MIMO transmission systems, multi-mode (MM) fibre offers the possibility to transmit different signals by different mode groups. In order to investigate the perspective of the MIMO philosophy within the field of optical transmission systems, channel measurements within a (2 × 2) MIMO system are carried out. For the channel measurements the second optical window and a fibre length of 1, 4 km was chosen. computer simulations on an overall data rate of 10, 24 Gbps underline the potential of multi-mode fibres in optical high-data rate MIMO communication systems and show that in order to achieve the best bit-error rate, not necessarily all MIMO layers have to be activated.
This paper gives a solution to the problem of verifying stability of networks consisting of integral input-to-state stable (iISS) subsystems. The iISS small-gain theorem developed recently has been restricted to inter...
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Phase change memory (PCM) is emerging as a promising solution for future memory systems and disk caches. As a type of resistive memory, PCM relies on the electrical resistance of Ge 2 Sb 2 Te 5 (GST) to represent sto...
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Phase change memory (PCM) is emerging as a promising solution for future memory systems and disk caches. As a type of resistive memory, PCM relies on the electrical resistance of Ge 2 Sb 2 Te 5 (GST) to represent stored information. With the adoption of multi-level programming PCM devices, unwanted resistance drift is becoming an increasing reliability concern in future high-density, multi-level cell PCM systems. To address this issue without incurring a significant storage and performance overhead in ECC, conventional design employs a conservative approach, which increases the resistance margin between two adjacent states to combat resistance drift. In this paper, we show that the wider margin adversely impacts the low-power benefit of PCM by incurring up to 2.3X power overhead and causes up to 100X lifetime reduction, thereby exacerbating the wear-out issue. To tolerate resistance drift, we proposed Helmet, a multi-level cell phase change memory architecture that can cost-effectively reduce the readout error rate due to drift. Therefore, we can relax the requirement on margin size, while preserving the readout reliability of the conservative approach, and consequently minimize the power and endurance overhead due to drift. Simulation results show that our techniques are able to decrease the error rate by an average of 87%. Alternatively, for satisfying the same reliability target, our schemes can achieve 28% power savings and a 15X endurance enhancement due to the reduced margin size when compared to the conservative approach.
Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was bui...
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Abstract This paper describes the development of an active vibration control system for a light and flexible stress ribbon footbridge. The 13 m span Carbon Fiber Reinforced Plastics (CFRP) stress ribbon bridge was built in the laboratory of the department of Civil and Structural engineering, Berlin Institute of Technology. Its lightness and flexibility result in high vibration sensitivity. To reduce pedestrian-induced vibrations, very light pneumatic muscle actuators are placed at handrail level introducing control forces. First, a reduced discretized analytical model is derived for the stress ribbon bridge. To verify the analytical prediction, experiments without feedback control are conducted. Based on this model, a velocity feedback control strategy is designed to actively control first mode vibrations. To handle the nonlinearities of the muscle actuator a subsidiary nonlinear force controller is implemented based on exact linearisation methods. The stability of the entire closed-loop system with actuator saturation is investigated by the Popov Criterion. Control performance is verified by experiments. It is demonstrated that handrail introduced forces can efficiently control the first mode response.
Spectacle computing is a novel strategy for vibrantly projecting information into the public sphere using expressive and tangible media. We demonstrate an example of this computing meme with large, glowing balloons th...
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A problem of assessing stability of retarded dynamical networks is solved in this paper. Subsystems are assumed to be integral input-to-state stable (iISS). Time-delays are allowed to reside in both subsystems and int...
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In this paper, the public techniques of the Internet of Things are studied, then the application prospect of the Internet of Things is established, after that, encoding card is designed to collect video, and monitor s...
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There is major interest within the bio-engineering community in developing accurate and non-invasive means for visualizing, modeling and analyzing bone micro-structures. Bones are composed of hierarchical bio-composit...
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There is major interest within the bio-engineering community in developing accurate and non-invasive means for visualizing, modeling and analyzing bone micro-structures. Bones are composed of hierarchical bio-composite materials characterized by complex multi-scale structural geometry. The process of reconstructing a volumetric bone model is usually based upon CT/MRI scanned images. Meshes generated by current commercial CAD systems cannot be used for further modeling or analysis. Moreover, recently developed methods are only capable of capturing the micro-structure for small volumes (biopsy samples). This paper examines the problem of re-meshing a 3D computerized model of bone micro- structure. The proposed method is based on the following phases: defining sub-meshes of the original model in a grid-based structure, remeshing each sub-mesh using the neural network (NN) method, and merging the sub-meshes into a global mesh. Applying the NN method to micro-structures proved to be quite time consuming. Therefore, a parallel, grid-based approach was applied, yielding a simpler structure in each grid cell. The performance of this method is analyzed, and the method is demonstrated on real bone micro-structures. Furthermore, the method may be used as the basis for generating a multi-resolution bone geometric model.
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