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Parallel and Distributed Computing (PDC) has become pervasive and is now exercised on a variety of platforms. Therefore, understanding how parallelism and distributed computing affect problem solving is important for every computing and engineering professional. However, most students in computer science (CS) and computer engineering (CE) programs are still introduced to computational problem solving using an old model, in which all processing is serial and synchronous, with input and output via text using a terminal interface or a local file system. Teaching a range of PDC knowledge and skills at multiple levels in Computer Science (CS) and related Computing and Engineering curricula is essential. The challenges are significant and numerous. Although some progress has been made in terms of curriculum recommendations and educational resources in computer science, trained faculty, motivation, and inertia are still some of the major impediments to introducing PDC early in computing curricula. The authors of this paper conducted a series of week-long faculty training workshops on the integration of PDC topics in CS1 and CS2 classes, and this paper provides an experience report on the impact and effectiveness of these workshops. Our survey results indicate such faculty development workshops can be effective in gradual inclusion of PDC in early computing curricula. 

Employers seek recruits who can apply the knowledge, skill, and culture they acquire in college to solve problems as soon as they enter the workforce. 

Welcome to the 4 th Workshop on Education for High Performance Computing (EduHiPC 2022). The EduHiPC 2022 workshop, held in conjunction with the IEEE International Conference on High Performance Computing Data & Analytics (HiPC 2022), is devoted to the development and assessment of educational and curricular innovations and resources for undergraduate and graduate education in Parallel and Distributed Computing (PDC) and High Performance Computing (HPC). EduHiPC brings together individuals from academia, industry, and other educational and research institutes to explore new ideas, challenges, and experiences related to PDC pedagogy and curricula. The workshop is designed in coordination with the IEEE TCPP curriculum initiative on parallel and distributed computing ( hitps://tcpp.cs.gsu .edu/curriculum/) for undergraduates majoring in computer science and computer engineering. It is supported by C-DAC, India and the US National Science Foundation (NSF) supported Center for Parallel and Distributed Computing Curriculum Development and Educational Resources (CDER). Details for attending the workshop are available on the HiPC webpage (HiPC). The effect of pandemic on academic and research community seems now to be globally receding as was evident from the enthusiastic in-person participation of conference delegates. Please visit the EduHiPC-22 webpage for the complete online proceedings, including copies of papers and presentation slides: EduHiPC 2022 | NSF/IEEE-TCPP Curriculum Initiative. 

As part of a 3-day workshop on training faculty members in concurrency, we developed a module for hands-on training in Java Fork-Join abstractions that had several related novel pedagogical and technical components: (1) Source and runtime checks that (a) tested whether test-aware code created by the trainees met the expected requirements and (b) logged their results in the local file system and the IBM cloud. (2) Editable worked example code along with a guide on how to understand the underlying concepts behind the code and experiment with the code. (3) The ability to follow the guide (a) synchronously, with graduate student help, in a session devoted to this module, and (b) asynchronously, on one's own, before or after the synchronous session. (4) Assignments trainees could do after experimenting with the worked example. (5) Zoom recording of the entire synchronous session. Fourteen faculty members across the country attended the session and had varying amounts of knowledge of Java and automatic assessment. Data gathered from check logs and a Zoom recording, together with novel visualizations of them, provide information to evaluate our pedagogical model and differentiate the participants. 

As in-vehicle communication becomes more complex, the automotive community is exploring various architectural options such as centralized and zonal architectures for their numerous benefits. Common characteristics of these architectures include the need for high-bandwidth communication and security, which have been elusive with standard automotive architectures. Further, as automotive communication technologies evolve, it is also likely that multiple link-layer technologies such as CAN and Automotive Ethernet will co-exist. These alternative architectures promise to integrate these diverse sets of technologies. However, architectures that allow such co-existence have not been adequately explored. In this work we explore a new network architecture called Named Data Networking (NDN) to achieve multiple goals: provide a foundational security infrastructure and bridge different link layer protocols such as CAN, LIN, and automotive Ethernet into a unified communication system. We have created a proof-of-concept bench-top testbed using CAN HATS and Raspberry PIs that replay real traffic over CAN and Ethernet to demonstrate how NDN can provide a secure, high-speed bridge between different automotive link layers. We also show how NDN can support communication between centralized or zonal high-power compute components. Security is achieved through digitally signing all Data packets between these components, preventing unauthorized ECUs from injecting arbitrary data into the network. We also demonstrate NDN's ability to prevent DoS and replay attacks between different network segments connected through NDN. 

Parallel and distributed computing (PDC) has become pervasive in all aspects of computing, and thus it is essential that students include parallelism and distribution in the computational thinking that they apply to problem solving, from the very beginning. Computer science education is still teaching to a 20th century model of algorithmic problem solving. Sequence, branch, and loop are taught in our early courses as the only organizing principles needed for algorithms, and we invest considerable time in showing how best to sequentially process large volumes of data. All computing devices that students use currently have multiple cores as well as a GPU in many cases. Most of their favorite applications use multiple cores and numbers of distributed processors. Often concurrency offers simpler solutions than sequential approaches. Industry is desperate for software engineers who think naturally in terms of exploiting these capabilities, rather than seeing them as an exotic upper-level topic that gets layered over a sequential solution. However, we are still teaching students to solve problems using sequential thinking. In this workshop we overview key PDC concepts and provide examples of how they may naturally be incorporated in early computing classes. We will introduce plugged and unplugged curriculum modules that have been successfully integrated in existing computing classes at multiple institutions. We will highlight the upcoming summer training workshop, for which we have funding to support attendance, as well as other CDER (Center for Parallel and Distributed Computing Curriculum Development and Educational Resources) activities.