37 research outputs found

    PADA: Power-aware development assistant for mobile sensing applications

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    � 2016 ACM. We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 developers to evaluate the usability of PADA. We show that developers benefit from using PADA in the implementation and power tuning of mobile sensing applications.N

    All-rounder: A flexible DNN accelerator with diverse data format support

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    Recognizing the explosive increase in the use of DNN-based applications, several industrial companies developed a custom ASIC (e.g., Google TPU, IBM RaPiD, Intel NNP-I/NNP-T) and constructed a hyperscale cloud infrastructure with it. The ASIC performs operations of the inference or training process of DNN models which are requested by users. Since the DNN models have different data formats and types of operations, the ASIC needs to support diverse data formats and generality for the operations. However, the conventional ASICs do not fulfill these requirements. To overcome the limitations of it, we propose a flexible DNN accelerator called All-rounder. The accelerator is designed with an area-efficient multiplier supporting multiple precisions of integer and floating point datatypes. In addition, it constitutes a flexibly fusible and fissionable MAC array to support various types of DNN operations efficiently. We implemented the register transfer level (RTL) design using Verilog and synthesized it in 28nm CMOS technology. To examine practical effectiveness of our proposed designs, we designed two multiply units and three state-of-the-art DNN accelerators. We compare our multiplier with the multiply units and perform architectural evaluation on performance and energy efficiency with eight real-world DNN models. Furthermore, we compare benefits of the All-rounder accelerator to a high-end GPU card, i.e., NVIDIA GeForce RTX30390. The proposed All-rounder accelerator universally has speedup and high energy efficiency in various DNN benchmarks than the baselines

    PowerForecaster: Predicting Smartphone Power Impact of Continuous Sensing Applications at Pre-installation Time

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    Today's smartphone application (hereinafter 'app') markets miss a key piece of information, power consumption of apps. This causes a severe problem for continuous sensing apps as they consume significant power without users' awareness. Users have no choice but to repeatedly install one app after another and experience their power use. To break such an exhaustive cycle, we propose PowerForecaster, a system that provides users with power use of sensing apps at pre-installation time. Such advanced power estimation is extremely challenging since the power cost of a sensing app largely varies with users' physical activities and phone use patterns. We observe that the time for active sensing and processing of an app can vary up to three times with 27 people's sensor traces collected over three weeks. PowerForecaster adopts a novel power emulator that emulates the power use of a sensing app while reproducing users' physical activities and phone use patterns, achieving accurate, personalized power estimation. Our experiments with three commercial apps and two research prototypes show that PowerForecaster achieves 93.4% accuracy under 20 use cases. Also, we optimize the system to accelerate emulation speed and reduce overheads, and show the effectiveness of such optimization techniques.

    Structure-Based Rational Design of a Toll-like Receptor 4 (TLR4) Decoy Receptor with High Binding Affinity for a Target Protein

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    Repeat proteins are increasingly attracting much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural features. Nonetheless, engineering interaction interface and understanding molecular basis for affinity maturation of repeat proteins still remain a challenge. Here, we present a structure-based rational design of a repeat protein with high binding affinity for a target protein. As a model repeat protein, a Toll-like receptor4 (TLR4) decoy receptor composed of leucine-rich repeat (LRR) modules was used, and its interaction interface was rationally engineered to increase the binding affinity for myeloid differentiation protein 2 (MD2). Based on the complex crystal structure of the decoy receptor with MD2, we first designed single amino acid substitutions in the decoy receptor, and obtained three variants showing a binding affinity (KD) one-order of magnitude higher than the wild-type decoy receptor. The interacting modes and contributions of individual residues were elucidated by analyzing the crystal structures of the single variants. To further increase the binding affinity, single positive mutations were combined, and two double mutants were shown to have about 3000- and 565-fold higher binding affinities than the wild-type decoy receptor. Molecular dynamics simulations and energetic analysis indicate that an additive effect by two mutations occurring at nearby modules was the major contributor to the remarkable increase in the binding affinities

    KRDS: a web server for evaluating drug resistance mutations in kinases by molecular docking

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    Abstract Kinases are major targets of anti-cancer therapies owing to their importance in signaling processes that regulate cell growth and proliferation. However, drug resistance has emerged as a major obstacle to cancer therapy. Resistance to drugs has various underlying mechanisms, including the acquisition of mutations at drug binding sites and the resulting reduction in drug binding affinity. Therefore, the identification of mutations that are relevant to drug resistance may be useful to overcome this issue. We hypothesized that these mutations can be identified by combining recent advances in computational methods for protein structure modeling and ligand docking simulation. Hence, we developed a web-based tool named the Kinase Resistance Docking System (KRDS) that enables the assessment of the effects of mutations on kinase-ligand interactions. KRDS receives a list of mutations in kinases, generates structural models of the mutants, performs docking simulations, and reports the results to users. The changes in docking scores and docking conformations can be analyzed to infer the effects of mutations on drug binding and drug resistance. We expect our tool to improve our understanding of drug binding mechanisms and facilitate the development of effective new drugs to overcome resistance related to kinases; it may be particularly useful for biomedical researchers who are not familiar with computational environments. Our tool is available at http://bcbl.kaist.ac.kr/KRDS/

    Optimization of Biomimetic Propulsive Kinematics of a Flexible Foil Using Integrated Computational Fluid Dynamics-Computational Structural Dynamics Simulations

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    A computational methodology, which combines a computational fluid dynamics (CFD) technique and a computational structural dynamics (CSD) technique, is employed to design a deformable foil whose kinematics is inspired by the propulsive motion of the fin or the tail of a fish or a cetacean. The unsteady incompressible Navier-Stokes equations are solved using a second-order accurate finite difference method and an immersedboundary method to effectively impose boundary conditions on complex moving boundaries. A finite element-based structural dynamics solver is employed to compute the deformation of the foil due to interaction with fluid. The integrated CFD-CSD simulation capability is coupled with a surrogate management framework (SMF) for nongradientbased multivariable optimization in order to optimize flapping kinematics and flexibility of the foil. The flapping kinematics is manipulated for a rigid nondeforming foil through the pitching amplitude and the phase angle between heaving and pitching motions. The flexibility is additionally controlled for a flexible deforming foil through the selection of material with a range of Young's modulus. A parametric analysis with respect to pitching amplitude, phase angle, and Young's modulus on propulsion efficiency is presented at Reynolds number of 1100 for the NACA 0012 airfoil.11Nsciescopu

    Noise Identification for an Automotive Wheel Bearing

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    In this study, we identified the noise generated from automotive wheel bearings, which has recently emerged as a new problem in electric vehicles. The wheel bearing assembly considered in this study consists of a wheel bearing, dust shield, and knuckle, which are fastened with bolts. To obtain the noise characteristics of the wheel bearing, the noise and vibration were experimentally measured when the bearing rotated. Additionally, the natural frequencies and mode shapes of the main components of the bearing were acquired via modal testing. By comparing the obtained natural frequencies with the peak frequencies of the measured noise and vibration signals, we identified where the noise radiated. To specifically identify bearing defects, a finite element analysis model was established, and the deformation of the bearing under load was analyzed. Based on the analysis, we determined that the deformation of the outer ring in an outboard row, which resulted from bolt fastening, leads to noise and vibration in the wheel bearing

    PADA: Power-aware development assistant for mobile sensing applications

    No full text
    � 2016 ACM. We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 developers to evaluate the usability of PADA. We show that developers benefit from using PADA in the implementation and power tuning of mobile sensing applications.N

    Noise Identification for an Automotive Wheel Bearing

    No full text
    In this study, we identified the noise generated from automotive wheel bearings, which has recently emerged as a new problem in electric vehicles. The wheel bearing assembly considered in this study consists of a wheel bearing, dust shield, and knuckle, which are fastened with bolts. To obtain the noise characteristics of the wheel bearing, the noise and vibration were experimentally measured when the bearing rotated. Additionally, the natural frequencies and mode shapes of the main components of the bearing were acquired via modal testing. By comparing the obtained natural frequencies with the peak frequencies of the measured noise and vibration signals, we identified where the noise radiated. To specifically identify bearing defects, a finite element analysis model was established, and the deformation of the bearing under load was analyzed. Based on the analysis, we determined that the deformation of the outer ring in an outboard row, which resulted from bolt fastening, leads to noise and vibration in the wheel bearing
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