Workload-aware Automatic Parallelization for Multi-GPU DNN Training

Deep neural networks (DNNs) have emerged as successful solutions for variety of artificial intelligence applications, but their very large and deep models impose high computational requirements during training. Multi-GPU parallelization is a popular option to accelerate demanding computations in DNN training, but most state-of-the-art multi-GPU deep learning frameworks not only require users to have an in-depth understanding of the implementation of the frameworks themselves, but also apply parallelization in a straight-forward way without optimizing GPU utilization. In this work, we propose a workload-aware auto-parallelization framework (WAP) for DNN training, where the work is automatically distributed to multiple GPUs based on the workload characteristics. We evaluate WAP using TensorFlow with popular DNN benchmarks (AlexNet and VGG-16), and show competitive training throughput compared with the state-of-the-art frameworks, and also demonstrate that WAP automatically optimizes GPU assignment based on the workload's compute requirements, thereby improving energy efficiency.Comment: This paper is accepted in ICASSP201

Hierarchical neural control of human postural balance and bipedal walking in sagittal plane

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 177-192).The cerebrocerebellar system has been known to be a central part in human motion control and execution. However, engineering descriptions of the system, especially in relation to lower body motion, have been very limited. This thesis proposes an integrated hierarchical neural model of sagittal planar human postural balance and biped walking to 1) investigate an explicit mechanism of the cerebrocerebellar and other related neural systems, 2) explain the principles of human postural balancing and biped walking control in terms of the central nervous systems, and 3) provide a biologically inspired framework for the design of humanoid or other biomorphic robot locomotion. The modeling was designed to confirm neurophysiological plausibility and achieve practical simplicity as well. The combination of scheduled long-loop proprioceptive and force feedback represents the cerebrocerebellar system to implement postural balance strategies despite the presence of signal transmission delays and phase lags. The model demonstrates that the postural control can be substantially linear within regions of the kinematic state-space with switching driven by sensed variables.(cont.) A improved and simplified version of the cerebrocerebellar system is combined with the spinal pattern generation to account for human nominal walking and various robustness tasks. The synergy organization of the spinal pattern generation simplifies control of joint actuation. The substantial decoupling of the various neural circuits facilitates generation of modulated behaviors. This thesis suggests that kinematic control with no explicit internal model of body dynamics may be sufficient for those lower body motion tasks and play a common role in postural balance and walking. All simulated performances are evaluated with respect to actual observations of kinematics, electromyogram, etc.by Sungho JoPh.D

Application of a model of cerebellar function to the maintenance of human upright posture

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2001.Includes bibliographical references (leaves 82-87).In this thesis a simple human postural control model is suggested and analyzed based on hypothesized neurophysiology of the cerebellar function and the musculoskeletal system. The cerebellum model is made up of simple linear filters such as differentiator and integrator. The simple linear filters implement a linear feedback control scheme including a phase lead compensator. The neural feedback signal represents the action of the cerebellum in the processing of angular position and angular velocity error signals. The goal of the investigation is to indicate whether the simple linear filters can describe neurophysiological functions of the cerebellum to compensate for the neural delays and coordinate the postural strategies that make possible human upright posture in gravity. Performance of the model is investigated with regard to disturbance rejection after adjustment of the parameters representing the cerebellum and the muscle. Whether the combination of the cerebellar and musculoskeletal control systems can realistically model human posture balance recovery is evaluated by simulating human postural maintenance during backward translation of a support surface. The simulation is compared with actual human postures and movements. The simulation realizes the ankle and hip strategy that prevails in human posture, and suggests the functions of the cerebellum.by Sungho Jo.S.M

Longitudinal association between adiposity changes and lung function deterioration

Background The longitudinal relationship between adiposity and lung function is controversial. We aimed to investigate the long-term association between adiposity changes and lung function in a middle-aged general Asian population. Methods In total, 5011 participants (average age, 54years; 45% men) were enrolled from a community-based prospective cohort. During the follow-up period (median 8years), both spirometry and bio-electrical impedance analysis were performed biannually. Individual slopes of the fat mass index (FMI; fat mass divided by the square of height in meters) and waist-to-hip ratio (WHR) were calculated using linear regression analysis. Multivariate linear mixed regression analysis was used to determine the long-term association between adiposity changes and lung function. Results The FMI was inversely associated with forced vital capacity (FVC) (estimated: − 31.8mL in men, − 27.8mL in women) and forced expiratory volume in 1s (FEV1) (estimated: − 38.2mL in men, − 17.8mL in women) after adjusting for baseline age, height, residential area, smoking exposure (pack-years, men only), initial adiposity indices, and baseline lung function. The WHR was also inversely associated with FVC (estimated = − 1242.2mL) and FEV1 (estimated = − 849.8mL) in men. The WHR-increased group showed a more rapid decline in lung function than the WHR-decreased group in both the fat-gain and fat-loss groups. Conclusion Adiposity was associated with the long-term impairment of lung function. Central obesity was the main driver of lung function impairment in the middle-aged general Asian population, regardless of fat mass changes

A huge intraductal papillary mucinous carcinoma of the bile duct treated by right trisectionectomy with caudate lobectomy

<p>Abstract</p> <p>Background</p> <p>Because intraductal papillary mucinous neoplasm of the bile duct (IPMN-B) is believed to show a better clinical course than non-papillary biliary neoplasms, it is important to make a precise diagnosis and to perform complete surgical resection.</p> <p>Case presentation</p> <p>We herein report a case of malignant IPMN-B treated by right trisectionectomy with caudate lobectomy and extrahepatic bile duct resection. Radiologic images showed marked dilatation of the left medial sectional bile duct (B4) resulting in a bulky cystic mass with multiple internal papillary projections. Duodenal endoscopic examination demonstrated very patulous ampullary orifice with mucin expulsion and endoscopic retrograde cholangiogram confirmed marked cystic dilatation of B4 with luminal filling defects. These findings suggested IPMN-B with malignancy potential. The functional volume of the left lateral section was estimated to be 45%. A planned extensive surgery was successfully performed. The remnant bile ducts were also dilated but had no macroscopic intraluminal tumorous lesion. The histopathological examination yielded the diagnosis of mucin-producing oncocytic intraductal papillary carcinoma of the bile duct with poorly differentiated carcinomas showing neuroendocrine differentiation. The tumor was 14.0 × 13.0 cm-sized and revealed no stromal invasiveness. Resection margins of the proximal bile duct and hepatic parenchyma were free of tumor cell. The patient showed no postoperative complication and was discharged on 10^thpostoperative date. He has been regularly followed at outpatient department with no evidence of recurrence.</p> <p>Conclusion</p> <p>Considering a favorable prognosis of IPMN-B compared to non-papillary biliary neoplasms, this tumor can be a good indication for aggressive surgical resection regardless of its tumor size.</p

Review of machine learning methods in soft robotics

Soft robots have been extensively researched due to their flexible, deformable, and adaptive characteristics. However, compared to rigid robots, soft robots have issues in modeling, calibration, and control in that the innate characteristics of the soft materials can cause complex behaviors due to non-linearity and hysteresis. To overcome these limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft sensors, soft actuators, and applications such as soft wearable robots. An analysis of the trends of different machine learning approaches with respect to different types of soft robot applications is presented; in addition to the current limitations in the research field, followed by a summary of the existing machine learning methods for soft robots