Short Courses of SSCAD 2025
Keywords:
Large Language Models, LLMs, Computer Architecture, Prompt Engineering, Jupyter Notebook, Google Colab, Data Science, Machine Learning, High-Performance Computing, Advanced Computer Architectures, RISC-V, LLVM Compiler, Open MPI 5.0, Message Passing Interface, MPI, Modular Component Architecture, MCA, Valgrind, Memchecker, Parallel ApplicationsSynopsis
This edition of the Short Courses of SSCAD 2025 compiles the instructional material prepared by the authors of the three tutorials presented during the 26th Symposium on High-Performance Computing Systems (SSCAD), held from October 28 to 31, 2025, in Bonito, MS.
The first tutorial proposes a practical approach for using Large Language Models (LLMs) as a support tool for developing instructional materials and conducting research in the areas of Computer Architecture and High-Performance Computing. The chapter presents fundamental concepts of prompt engineering, details the functionality of major interactive notebook software—Jupyter Notebook and Google Colab—used for code development and execution, and provides interactive examples of systems built with LLMs. The examples explore topics such as data science, machine learning, high-performance computing, as well as advanced, dedicated, and specialized computer architectures, along with evaluation methods and performance measurement and prediction.
The second tutorial offers a detailed guide on adding new instructions to the RISC-V backend of the LLVM compiler infrastructure. The tutorial describes step-by-step the design of a small extension called “xmatrix,” which introduces 32 dedicated 512-bit matrix registers (4 × 4 matrices of 32-bit elements) and a limited set of arithmetic and load/store operations.
Finally, the third tutorial discusses the Open MPI 5.0 mechanisms—one of the most widely used APIs in the development of parallel applications in high-performance environments—that simplify debugging and fine-tuning activities. The content begins with a brief introduction to MPI (Message Passing Interface), followed by a detailed explanation of the Modular Component Architecture (MCA), which provides developers with an extensive set of options for tuning and debugging MPI programs. The chapter concludes with practical aspects of the tuning process, including the use of Valgrind and Memchecker tools for debugging parallel applications.
We believe that this book will enable students, researchers, professionals, and enthusiasts in the fields of Computer Architecture and High-Performance Computing to gain consistent and in-depth access to the knowledge presented at SSCAD 2025, offering a solid, clear, and long-lasting resource for advancing their studies—even for those who were unable to attend the event in person.
Chapters
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1. Increased Productivity with LLMs, Prompt Engineering, Machine Learning, and GPUs
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2. Implementing new RISC-V Instructions with the LLVM Compiler Infrastructure
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3. Tuning and debugging applications in Open MPI 5.0
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References
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