2022 Topics on Mathematical and Computing Science B

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Academic unit or major
Graduate major in Mathematical and Computing Science
Ishizaki Kazuaki  Inagaki Tatsushi  Inoue Hiroshi  Ogata Kazunori  Onodera Tamiya  Kawachiya Kiyokuni  Nakaike Takuya  Horii Hiroshi  Horie Michihiro  Le Duc Tung 
Class Format
Lecture    (Face-to-face)
Media-enhanced courses
Day/Period(Room No.)
Mon5-6(H116)  Thr5-6(H116)  
Course number
Academic year
Offered quarter
Syllabus updated
Lecture notes updated
Language used
Access Index

Course description and aims

This course covers advanced topics on implementation of programming languages. The topics include runtime systems, dataflow analysis, inlining, deep learning compiler, JVM, LLVM.

This lecture is held on 5 and 6 time slots (13:45-15:25) on every Monday and Thursday, starting on Dec. 8. For the detailed schedule , please check the Japanese version of syllabus. We use lecture room H116.

Student learning outcomes

By the end of this course, students will understand the state-of-art technologies on implementation of programming languages.


programming language, compiler, runtime system, JVM, LLVM

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

Each class offers a standard type of lecture.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Runtime – JVM Overview & Interpreter Understand the concepts of runtime systems
Class 2 Runtime – Object Management & Synchronization Understand the concepts of object management & synchronization
Class 3 Runtime – Native Memory Management Understand the basic techniques of native memory management
Class 4 Compiler – Overview Understand the overall structure of compilers
Class 5 Compiler – Dataflow Analysis Understand the theory and practice of dataflow analysis
Class 6 Compiler – Devirtualization & Inlining Understand the basic techniques of devirtualization & inlining
Class 7 Hot topic – H/W Acceleration (GPGPU, HTM, FPGA) Understand the advantages and disadvantages of H/W acceleration
Class 8 Hot topic – Open Source Java VM Understand the current status and techniques of open source JVM
Class 9 Compiler – Trace Compilation & LLVM Understand the techniques in trace compilation & LLVM
Class 10 Hot topic – Deep Learning Compiler & MLIR (given in English) Understand the concepts of deep learning compiler & MLIR
Class 11 Hot topic – Compiler in Quantum Computer Understand the role of compilers in processing quantum applications
Class 12 Concluding Remarks & Outlook Understand the ongoing issues of compiler technologies

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.


Textbooks will not be used in this course.

Reference books, course materials, etc.

References will be announced in classes.

Assessment criteria and methods

This lecture is graded by two reports.

Related courses

  • MCS.T334 : Compiler Construction

Prerequisites (i.e., required knowledge, skills, courses, etc.)

Basic knowledge on compilation of programming languages.

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