STRUMM: An Intelligent, Adaptive Software Package for Older Adults With a Cognitive Impairment

Many older adults have a cognitive impairment (CI), which negatively impacts on their quality of life and threatens their independence. In this presentation, we provide an overview of the conceptual framework, structure, and processes of our multi-site Center, ENHANCE, which is focused on developing technology support for aging adults with a CI. ENHANCE has two cross-site research projects, two cross-site development projects, training, and dissemination components. A core battery of measures is collected across all projects. We also discuss the Supportive Technology Resources through Usability & Machine-learning Methods (STRUMM) research project, which focuses on an innovative intelligent adaptive software package aimed at providing cognitive and social support, and support for resource access to aging adults with a CI. STRUMM is designed to meet the user’s varying cognitive needs. Finally, we present preliminary data regarding the perceived usability and value of STRUMM from our clinical partners and potential user groups.

Study of appropriate offload destination based on software arithmetic intensity

IEICE Technical Workshop on Network Software, BS-26-2.I have proposed environment-adaptive software that automatically converts the description code according to the destination device and operates it with high performance. Currently, for environments where GPUs, FPGAs, and manycore CPUs are mixed in the cloud or so on, all offload destination performance is verified and the fastest migration destination is selected, and it takes a long time. In this paper, I use the Arithmetic Intensity of the application loop statement to verify whether it is possible to select for GPU or manycore CPU.

Initial study of environment-adaptive application placement optimization

IEICE Technical Workshop on Network Software, BS-25-2.I have proposed environment adaptive software that automatically converts, resource settings, and deploys the code once written according to the deployment destination environment hardware, and operates it with high performance. I also have been working on automatic conversion of code to GPU and FPGA. In this paper, I initially examine an appropriate placement method that satisfies the user's requirements and reduces the cost, response time and so on of an application that has been automatically converted so that it can be placed on GPU or FPGA.

Study of Automatic Offloading Method in Mixed Offloading Destination Environment 移行先混在環境における自動オフロード方式の検討

IEICE Technical Report, IN2020-30.In recent years, utilization of heterogeneous hardware other than small core CPU such as GPU, FPGA or many core CPU is increasing. However, when using heterogeneous hardware, barriers of technical skills such as OpenMP, CUDA and OpenCL are high. Based on that, I have proposed environment-adaptive software that enables automatic conversion, configuration, and high performance operation of once written code, according to the hardware to be placed. However, including existing technologies, there has been no research to properly and automatically offload the mixed offloading destination environment such as GPU, FPGA and many core CPU. In this paper, as a new element of environment-adaptive software, I study a method for offloading applications properly and automatically in the environment where the offloading destination is mixed with GPU, FPGA and many core CPU. I evaluate the effectiveness of the proposed method in multiple applications.

Study of Automatic FPGA Offloading for Loop Statements of Applications

IEICE technical workshop on Network Software, NWS-19-6.Recently, heterogeneous hardware such as GPU and FPGA is used in many systems and also IoT devices are increased rapidly. However, to utilize heterogeneous hardware, the hurdles are high because of much technical skills. I have proposed environment adaptive software to operate an once written application with high performance by automatically converting the code and configuring setting so that we can utilize GPU, FPGA and IoT devices in the location to be deployed and I have also achieved automatic GPU offloading partly. In this paper, I study a method of FPGA offloading which automatically extracts appropriate loop statements of application software.

A Holistic Self-Adaptive Software Model

The recent self-adaptive software systematic literature reviews stated clearly the following insufficiencies: (1) the need for a holistic self-adaptive software model to integrate its different aspects (2) The limitation of adaptations to context changes (3) The absence of a general and complete adaptations’ picture allowing its understandability, maintainability, evaluation, reuse, and variability. (4) The need for an explicit and a detailed link with resources, and (5) a usual limitation to known events. In order to metigate these insufficiencies, this paper is proposing a holistic model that integrates the operating, adaptations, and adaptations’ manager aspects. The proposed model covers all possible adaptations: operating (dealing with software functions failures), lifecycle (handling adaptations required by some software lifecycle steps), and context (facing context changes events). The presented work introduces the concept of software adaptations process integrating the specifications of all the above kind of adaptations. In fact, this work shows an explicit trace to its pure bio-inspired origin.An application of the proposed approach on a “car industry case study” demonstrated its feasibility in comparison with similar works that proved its meaningful added value and its promising research perspectives.