PADA: Power-aware development assistant for mobile sensing applications

� 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

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

Reduction of coherent betatron oscillations in a muon g-2 storage ring experiment using RF fields

This work demonstrates that two systematic errors, coherent betatron oscillations (CBO) and muon losses can be reduced through application of radio frequency (RF) electric fields, which ultimately increases the sensitivity of the muon $g-2$ experiments. As the ensemble of polarized muons goes around a weak focusing storage ring, their spin precesses, and when they decay through the weak interaction, $\mu^+ \rightarrow e^+ \nu_e \bar{\nu_\mu}$, the decay positrons are detected by electromagnetic calorimeters. In addition to the expected exponential decay in the positron time spectrum, the weak decay asymmetry causes a modulation in the number of positrons in a selected energy range at the difference frequency between the spin and cyclotron frequencies, $\omega_\text{a}$. This frequency is directly proportional to the magnetic anomaly $a_\mu =(g-2)/2$, where $g$ is the g-factor of the muon, which is slightly greater than 2. The detector acceptance depends on the radial position of the muon decay, so the CBO of the muon bunch following injection into the storage ring modulate the measured muon signal with the frequency $\omega_\text{CBO}$. In addition, the muon populations at the edge of the beam hit the walls of the vacuum chamber before decaying, which also affects the signal. Thus, reduction of CBO and unwanted muon loss increases the $a_\mu$ measurement sensitivity. Numerical and experimental studies with RF electric fields yield more than a magnitude reduction of the CBO, with muon losses comparable to the conventional method.Comment: 14 pages, 25 figure

Sandra Helps You Learn: The More You Walk, The More Battery Your Phone Drains

Emerging continuous sensing apps introduce new major factors governing phones' overall battery consumption behaviors: (1) added nontrivial persistent battery drain, and more importantly (2) different battery drain rate depending on the user's different mobility condition. In this paper, we address the new battery impacting factors significant enough to outdate users' existing battery model in real life. We explore an initial approach to help users understand the cause and effect between their physical activity and phones' battery life. To this end, we present Sandra, a novel mobility-aware smartphone battery information advisor, and study its potential to help users redevelop their battery model. We perform an extensive explorative study and deployment for 30 days with 24 users. Our findings reveal what they essentially learned, and in which situations they found Sandra very helpful. We share the lessons learned to help in the design of future mobility-aware battery advisors.1

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

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

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

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

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

MOESM1 of KRDS: a web server for evaluating drug resistance mutations in kinases by molecular docking

Additional file 1: Table S1. Re-docking of five ligands co-crystalized with CDK2 to the five RosettaBackrub generated CDK2 conformations. Table S2. RMSD values after re-docking of co-crystals into native structures. Table S3. The list of pdb ids of DFG-in and its corresponding DFG-out structures to perform docking in ABL1, BRAF, EGFR, FGFR4, and IGF1R. Table S4. The averaged docking values of DFG-in and its corresponding DFG-out structures. Table S5. The maximum docking values obtained among ensembles. Table S6. The docking results of ABL1 and EGFR using GOLD. Table S7. The docking results of ABL1 and EGFR using AutoDock Vina. Table S8. Comparison of docking scores and kinase activity data in ABL1 and EGFR. Table S9. Tanimoto coefficient scores between two drugs. Figure S1. Re-docking of imatinib and erlotinib in ABL1 and EGFR. Figure S2. The results of re-docking ligands on different DFG states