EduHiPC 2024 Technical Program

Abstract: The field of AI (including Machine Learning (ML), Deep Learning (DL), Big Data, and Data Science) are rapidly evolving. The effective development and usage of many AI models and the associated inference schemes depend on a good understanding of the underlying HPC hardware and software technologies. Thus, it is becoming a challenge for students and professionals to have a holistic understanding of this new field. In this context, I will share experiences from the following four initiatives in which I am engaged with: 1) A semester long course on `High-Performance Deep/Machine Learning’ for combined undergraduate and graduate students at the Ohio State University; 2) A two series 14-week course (developed through an NSF funding) on 'AI Bootcamp for Cyberinfrastructure Professionals' working in many different HPC centers; 3) A Half-day/full-day conference tutorial on “Principles and Practice of High-Performance Deep/Machine Learning”, and 4) Nurturing Next-Gen students for democratizing AI through the NSF-funded ICICLE (icicle.ai) Institute. An overview of these initiatives and the associated approaches will be presented.

Speaker Bio: DK Panda is a Professor and University Distinguished Scholar of Computer Science and Engineering at the Ohio State University. He is serving as the Director of the ICICLE NSF-AI Institute (https://icicle.ai). He has published over 500 papers. The MVAPICH MPI libraries, designed and developed by his research group (http://mvapich.cse.ohio-state.edu), are currently being used by more than 3,400 organizations worldwide (in 92 countries). More than 1.83 million downloads of this software have taken place from the project's site. This software is empowering many clusters in the TOP500 list. High-performance and scalable solutions for Deep Learning frameworks and Machine Learning applications from his group are available from https://hidl.cse.ohio-state.edu. Similarly, scalable, and high-performance solutions for Big Data and Data science frameworks are available from https://hibd.cse.ohio-state.edu. Prof. Panda is an IEEE Fellow. He is a recipient of the 2022 IEEE Charles Babbage Award and the 2024 IEEE TCPP Outstanding Service and Contributions Award. More details about Prof. Panda are available at http://www.cse.ohio-state.edu/~panda.

Abstract: In this talk, I will present some of our research work on exploiting parallelism, starting from instruction-level parallelism in VLIW and superscalar processors to thread-level and task-level parallelisms in heterogeneous architectures involving CPU, GPUs and many-core architectures. The talk will also touch upon programming models that are useful in addressing programmability and productivity challenges in domain specific languages. Finally I will bring out the importance of research in the interface of architecture and compiler design and programming models for extracting performance, productivity and portability. I will also present how the research has led to design the curricula for an introductory course in High Performance Computing and a Parallel Programming for Computational Scientists . The research has also helped us identify and contribute in areas from Digital Signal Processing to Graph Analytics to Machine Learning.

Speaker Bio: R. Govindarajan received his B.Sc. degree in Mathematics from Madras University in 1981 and B.E. (Electronics and Communication) and Ph.D. (Computer Science) degrees from the Indian Institute of Science, Bangalore in 1984 and 1989 respectively. He has held postdoctoral research positions and visiting faculty positions at Universities in USA and Canada. Since 1995, he has been with the Supercomputer Education and Research Centre and the Department of Computer Science and Automation, Indian Institute of Science, Bangalore. His research interests are in the areas of High Performance Computing, Compilation Techniques, and Computer Architecture. He has more than 140 research publications in international journals and refereed conferences. He is a fellow of the Indian National Academy of Engineering, a Senior Member of the IEEE and a Distinguished Member of the ACC.

Abstract: Computational science is about solving scientific problems numerically which is a very well established field on it's own. With the rapid growth in the field of computer science and related computing technology, there is a growing need to bring practices from engineering analysis and design into the field of scientific simulation.

The primary driver behind the need is to develop scalable scientific simulation software with which one can target for higher throughput, not just high performance. This is exactly why a field like computational engineering (CE) has emerged. CE is that area where computational mathematics, domain specific science, core computer science and software engineering converge.

In this presentation, we will be explaining different corners and the rationale behind developing expertise in such a field with some real life examples covering all the areas that are the foundation of computational engineering, especially in the age where we are seeing a massive growth in the area of artificial intelligence (AI).

Speaker Bio: Chiranjib Sur is the Head of Engineering for Scientific Software at Shell. In his current role, he is responsible for the development of scalable scientific software based on the fundamental research that happens in different R&D labs of Shell across the globe. Starting his career as a computational physicist, Chiranjib has turned into a computer scientist with a specialization in numerical simulations, high-performance computing, and scalable AI. In his career spanning more than two decades, he has worked previously at the Indian Institute of Astrophysics, The Ohio State University (USA), and IBM, before joining Shell in 2012.

Chiranjib, a senior member of IEEE and ACM, is the recipient of the 2003 Young Scientist Medal from the Indian Science Congress Association. Externally, he chaired the IEEE's conference series on high-performance computing, data, and, analytics (www.hipc.org) from 2017-2023. He also serves in the advisory boards of several premier Indian academic institutions.