Effective Software

Relations:

During a review of study plans, the course A4M35OSP can be substituted for the course B4M36ESW.

It is not possible to register for the course B4M36ESW if the student is concurrently registered for or has already completed the course A4M35OSP (mutually exclusive courses).

It is not possible to register for the course B4M36ESW if the student is concurrently registered for or has already completed the course BE4M36ESW (mutually exclusive courses).

It is not possible to register for the course B4M36ESW if the student is concurrently registered for or has previously completed the course BE4M36ESW (mutually exclusive courses).

The requirement for course B4M36ESW can be fulfilled by substitution with the course BE4M36ESW.

Course guarantor:

David Šišlák

Lecturer:

Jakub Dupák, David Šišlák

Tutor:

Jakub Dupák, Tomáš Hauser, Lukáš Maruniak, David Šišlák

Supervisor:

Department of Computer Science

Synopsis:

Students will become familiar with the issues of software and algorithm optimization under limited resources. The course focuses on the efficient use of modern hardware architectures, namely multi-core and multiprocessor shared-memory systems. Students will learn to implement the techniques presented in the lectures in C and Java. The main topics include code optimization, efficient data structures and the use of CPU cache memory, data structures in multithreaded applications, and the implementation of high-performance network servers.

Requirements:

background knowledge in area of Computer architecture, C and Java programming languages

Syllabus of lectures:

1. Introduction, modern computer architecture, C compilers.

2. Bentley's rules, C compiler, profiling.

3. Benchmarking, measurements, metrics, statistics, WCET, timestamping.

4. Scalable synchronization from mutexes to RCU (read-copy-update), transactional memory, scalable API.

5. Memory access efficient programming with caches, dynamic memory allocation (malloc, NUMA, ...)

6. Serialization of data structures JSON, XML, protobufs, AVRO, cap'n'proto, mmap/shared memory.

7. Program run virtual machine, byte-code, Java compiler, JIT compiler, relation to machine code, byte-code analysis, dissasembly of Java byte-code, optimization in compilers, program performance analysis, profiling.

8. Data concurrency in JVM multi-threaded access to data, locks monitoring, atomic operations, lock-less/block-free data structures, non-blocking algorithms (queue, stack, set, dictionary), data races, synchronization.

9. Efficient servers, C10K, non-blocking I/O, efficient networking, threads.

10. JVM Memory analysis (dynamic/static), data structures, collections for performance.

11. JVM Object allocation, bloom filters, references, effective caching.

12. Virtualization (IOMMU, SR-IOV, PCI pass-through, virtio, ).

13. Memory Management in JVM Memory Layout, Garbage Collectors.

Syllabus of tutorials:

Study Objective:

Study materials:

[1] MIT: Performance-engineering-of-software-systems

[2] Oaks, S.: Java Performance: 2nd Edition. O'Reilly, USA 2020.

[3] Jones, R., Hosking, A., Moss, E.: The Garbage Collection Handbook - The Art of Automatic Memory Management. CRC Press, USA 2012.

[4] Herlihy, M., Shavit, N.: The Art of Multiprocessor Programming. Morgan Kaufman, 2008.

[5] Fog, A.: The microarchitecture of Intel, AMD and VIA CPU, 2016.

[6] Drepper U.: What every programmer should know about memory, 2007

[7] Jain, R.: The Art of Computer Systems Performance Evaluation. Wiley, New York 1991. (slides, book)

[8] Lilja, D. J.: Measuring Computer Performance: A Practitioner?s Guide. Cambridge University Press, 2000. (book web site, Supplemental Teaching Materials)

Note:

Further information:

https://esw.pages.fel.cvut.cz/

Time-table for winter semester 2025/2026:

Time-table is not available yet

Time-table for summer semester 2025/2026:

	06:00–08:0008:00–10:0010:00–12:0012:00–14:0014:00–16:0016:00–18:0018:00–20:0020:00–22:0022:00–24:00
Mon	roomKN:E-301 Šišlák D. Dupák J. 12:45–14:15 (lecture parallel1) Karlovo nám. roomKN:E-310 Hauser T. Maruniak L. 16:15–17:45 (lecture parallel1 parallel nr.101) Karlovo nám. roomKN:E-307 Hauser T. Maruniak L. 14:30–16:00 (lecture parallel1 parallel nr.102) Karlovo nám. roomKN:E-311 Hauser T. Maruniak L. 16:15–17:45 (lecture parallel1 parallel nr.103) Karlovo nám.
Tue
Wed
Thu
Fri

The course is a part of the following study plans:

• Open Informatics - Computer Engineering 2018 (compulsory course of the specialization)
• Open Informatics - Software Engineering 2018 (compulsory course of the specialization)
• Open Informatics - Computer Engineering 2026 (PS)
• Open Informatics - Software Engineering 2026 (PS)