Stochastic models for quality of service of component connectors

The intensifying need for scalable software has motivated modular development and using systems distributed over networks to implement large-scale applications. In Service-oriented Computing, distributed services are composed to provide large-scale services with a specific functionality. In this way, reusability of existing services can be increased. However, due to the heterogeneity of distributed software systems, software composition is not easy and requires additional mechanisms to impose some form of a coordination on a distributed software system. Besides functional correctness, a composed service must satisfy various quantitative requirements for its clients, which are generically called its quality of service (QoS). Particularly, it is tricky to obtain the overall QoS of a composed service even if the QoS information of its constituent distributed services is given. In this thesis, we propose Stochastic Reo to specify software composition with QoS aspects and its compositional semantic models. They are also used as intermediate models to generate their corresponding stochastic models for practical analysis. Based on this, we have implemented the tool Reo2MC. Using Reo2MC, we have modeled and analyzed an industrial software, the ASK system. Its analysis results provided the best cost-effective resource utilization and some suggestions to improve the performance of the system.UBL - phd migration 201

A Compositional Semantics for Stochastic Reo Connectors

In this paper we present a compositional semantics for the channel-based coordination language Reo which enables the analysis of quality of service (QoS) properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo automata to Continuous-Time Markov Chains (CTMCs). This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499

Fragility Analysis of Space Reinforced Concrete Frame Structures with Structural Irregularity in Plan

Because significant damages to structures having structural irregularity in their plans were repeatedly observed during many past earthquakes, there have been great research efforts to evaluate their seismic vulnerability. Although most of the previous studies used simplified structural representations such as one-dimensional or two-dimensional models in the fragility analysis of plan-irregular structures, simple analytical models could not represent true seismic behavior from the complicated nonlinear coupling between lateral and torsional responses as the degree of irregularity increased. For space structures with high irregularity, more realistic representations such as three-dimensional models are needed for proper seismic assessment. However, the use of computationally expensive models is not practically feasible with existing approaches of fragility analysis. Thus, in this study, a different approach is adopted that can produce vulnerability curves efficiently, even with a three-dimensional model. In this approach, an integrated computational framework is established that combines reliability analysis and structural analysis. This enables evaluation of the limit-state faction without constructing its explicit formula, and the failure probability is calculated with the first-order reliability method (FORM) to deal with the computational challenge. Under the integrated framework, this study investigates the seismic vulnerability of space reinforced concrete frame structures with varying plan irregularity. Material uncertainty is considered, and more representative seismic fragility curves are derived with their three-dimensional analytical models. The effectiveness of the adopted approach is discussed, and the significant effect of structural irregularity on seismic vulnerability is highlighted

Simple coordination complex-derived three-dimensional mesoporous graphene as an efficient bifunctional oxygen electrocatalyst

3D mesoporous graphene (mesoG) was synthesized from [Ni<inf>2</inf>(EDTA)] (EDTA = ethylenediaminetetraacetate). The material is comprised of interconnected 4 nm-sized hollow carbon shells composed of 3-4 layers of graphene and exhibits high bifunctional electrocatalytic activity as well as high durability for use in oxygen evolution and reduction reactions. This journal is ??? 2015 The Royal Society of Chemistryopen11

Stochastic reo: a case study

QoS analysis of coordinated distributed autonomous services is currently of interest in the area of service-oriented computing and calls for new technologies and supporting tools. In previous work, the first three authors have proposed a compositional automata model to provide semantics for stochastic Reo, a channel based coordination language that supports the specification of QoS values (such as request arrivals or processing rates). Furthermore, translations from this automata model into stochastic models, such as continuous-time Markov chains (CTMCs) and interactive Markov chains (IMCs) have also been presented. Based on those results, we describe in this paper a case study of QoS analysis. We analyze a certain instance of the ASK system, an industrial software system for connecting people offering professional services to clients requiring those services. We develop a model of the ASK system using stochastic Reo. The distributions used in this model were obtained by applying statistical analysis techniques on the raw values that we obtained from the real logs of an actual running ASK system. These distributions are used for the derived CTMC model for the ASK system to analyze and to improve the performance of the system, under the assumption that the distributions are exponentially distributed. In practice, this is not always the case. Thus, we also carry out a simulation-based analysis by a Reo simulator that can deal with non-exponential distributions. Compared to the analysis on the derived CTMC model, the simulation is approximation-based analysis, but it reveals valuable insight in the behavior of the system. The outcome of both analyses helps both the developers and the installations of the ASK system to improve the performance of the system

In Vitro Chemosensitivity Using the Histoculture Drug Response Assay in Human Epithelial Ovarian Cancer

The choice of chemotherapeutic drugs to treat patients with epithelial ovarian cancer has not depended on individual patient characteristics. We have investigated the correlation between in vitro chemosensitivity, as determined by the histoculture drug response assay (HDRA), and clinical responses in epithelial ovarian cancer. Fresh tissue samples were obtained from 79 patients with epithelial ovarian cancer. The sensitivity of these samples to 11 chemotherapeutic agents was tested using the HDRA method according to established methods, and we analyzed the results retrospectively. HDRA showed that they were more chemosensitive to carboplatin, topotecan and belotecan, with inhibition rates of 49.2%, 44.7%, and 39.7%, respectively, than to cisplatin, the traditional drug of choice in epithelial ovarian cancer. Among the 37 patients with FIGO stage Ⅲ/Ⅳ serous adenocarcinoma who were receiving carboplatin combined with paclitaxel, those with carboplatin-sensitive samples on HDRA had a significantly longer median disease-free interval than patients with carboplatin- resistant samples (23.2 vs. 13.8 months, p＜0.05), but median overall survival did not differ significantly (60.4 vs. 37.3 months, p＝0.621). In conclusion, this study indicates that HDRA could provide useful information for designing individual treatment strategies in patients with epithelial ovarian cancer

DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation

Transformer is a deep learning language model widely used for natural language processing (NLP) services in datacenters. Among transformer models, Generative Pre-trained Transformer (GPT) has achieved remarkable performance in text generation, or natural language generation (NLG), which needs the processing of a large input context in the summarization stage, followed by the generation stage that produces a single word at a time. The conventional platforms such as GPU are specialized for the parallel processing of large inputs in the summarization stage, but their performance significantly degrades in the generation stage due to its sequential characteristic. Therefore, an efficient hardware platform is required to address the high latency caused by the sequential characteristic of text generation. In this paper, we present DFX, a multi-FPGA acceleration appliance that executes GPT-2 model inference end-to-end with low latency and high throughput in both summarization and generation stages. DFX uses model parallelism and optimized dataflow that is model-and-hardware-aware for fast simultaneous workload execution among devices. Its compute cores operate on custom instructions and provide GPT-2 operations end-to-end. We implement the proposed hardware architecture on four Xilinx Alveo U280 FPGAs and utilize all of the channels of the high bandwidth memory (HBM) and the maximum number of compute resources for high hardware efficiency. DFX achieves 5.58x speedup and 3.99x energy efficiency over four NVIDIA V100 GPUs on the modern GPT-2 model. DFX is also 8.21x more cost-effective than the GPU appliance, suggesting that it is a promising solution for text generation workloads in cloud datacenters.Comment: Extension of HOTCHIPS 2022 and accepted in MICRO 202

KINEMATIC COMPARISONS OF KETTLEBELL TWO-ARM SWINGS BETWEEN EXPERTS AND BEGINNERS

The purpose of this study was to investigate kinematic comparisons of kettlebell two-arm swings between experts and beginners in order to find out biomechanical key points for preventing sports injuries and enhancing kettlebell performance. Four experts and three beginners performed kettlebell two-arm swings fifteen times with a 16 kg kettlebell. Experts demonstrated larger ranges of motions (ROM) of pelvic segment and hip joint than beginners, while beginners revealed larger ROM of shoulder joint than experts. Magnitudes and sequential orders of peak angular velocities of major joints were significantly different between two groups. Conclusively, the mobility of pelvic segment and hip joint are required, while the stability of the other joint are needed to produce appropriate kettlebell two-arm swings. The activation and strength of gluteus muscles would be key contributors