IRES: U.S.-Hungary Research Experience for Students on Non-Boolean Computer Architectures

这个美国-匈牙利项目的目标是为美国学生提供早期职业国际研究经验（IRES），他们将学习基于细胞神经网络（CNN）的新兴技术，目标是增强和开发信息处理系统。IRES项目活动将在布达佩斯举行，由首席研究员Michael Niemier监督，并与圣母大学的同事和Pázmány psamter Catholic University （PPKE）的教员合作。CNN是一种模拟阵列处理器架构，旨在显著提高各种计算密集型应用的功率和性能，如图像处理、模式识别和运动检测。美国和匈牙利的团队将共同寻求有效的方法，摆脱芯片存储的程序模型。通过寻求额外的功能和能力，研究导师和他们的学生希望利用新的信息处理技术和算法来进一步增强CNN范式的功能和应用空间。技术总结：通过圣母大学和匈牙利布达佩斯Pázmány psamter Catholic University （PPKE）教师的合作和指导，IRES学生参与者将讨论新兴技术对架构、算法和编程的影响。合作研究活动将侧重于确定以类似cnn的方式组织的新兴设备技术是否可以“编程”，是否适合基于模板的操作。美国学生参与者和他们的PPKE同行将研究现有的硬件设计，以便通过新兴技术（可能是通过更低的能耗）进行改进，如果可能的话，研究对可编程性的影响。例如，将探索目前仅存在于数学上的新的cnn计算模型（例如，无帧计算和基于延迟的模板）的硬件实现的可行性。对于新的应用领域，团队将以触觉传感为目标，重点开发集成传感技术的CNN电路。同样感兴趣的是基于石墨烯的电子产品和开发算法来处理感测数据。如果成功，美国-匈牙利IRES团队的联合研究活动可能会引导我们考虑新的，集成传感和触觉数据处理技术，用于潜在的更重负载应用领域，如机器人或假肢脚。

The objective of this U.S.-Hungarian project is to provide early career international research experience (IRES) for U.S. students who will study emerging technologies based on cellular neural networks(CNN)with the goal of enhancing and developing information processing systems. The IRES program of activities will take place in Budapest, overseen by the principal investigator, Michael Niemier, in partnership with colleagues from the University of Notre Dame and faculty at Pázmány Péter Catholic University (PPKE). A CNN is an analog array processor architecture designed to significantly improve the power and performance of various computation-intensive applications, such as image processing, pattern recognition, and motion detection. Together, the U.S.-Hungarian team will pursue effective ways to move away from chip stored program models. By seeking additional functionalities and capabilities, the research mentors and their students expect to leverage new information processing technologies and algorithms to further enhance the functionality of and application spaces for the CNN paradigm.Technical Summary:Via collaboration and mentoring by faculty from the University of Notre Dame and Pázmány Péter Catholic University (PPKE) in Budapest, Hungary, the impact of emerging technologies on architectures, algorithms, and programming will be addressed by IRES student participants. Cooperative research activity will focus on determining whether emerging device technologies that are organized in a CNN-like fashion can be "programmed" and are amenable to template-based operations. U.S. student participants and their PPKE counterparts will study existing hardware designs for improvement by emerging technologies, possibly via lower energy, and if likely, what the resulting impact on programmability will be. For example, the viability of hardware realizations of new CNN-computing models (e.g., frameless computing and delay-based templates) that presently exist only mathematically will be explored. For new application spaces, team efforts will target tactile sensing and focus on developing CNN circuitry with integrated sensing technology. Also of interest are graphene based electronics and developing algorithms to process sensed data. If successful, the U.S.-Hungarian IRES team's combined research activities may lead us to consider new, integrated sensing and tactile data processing techniques for potential heavier load applications in areas such as robots or prosthetic feet.