CS509 Advanced Computer Architecture
CS509 Advanced Computer Architecture
Syllabus | International University of Sarajevo - Last Update on Oct 10, 2025
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Computer Sciences and Engineering
Amal Mersni
Course Lecturer
Course Objectives
This course dives deep into the design principles and performance breakthroughs powering today’s most innovative systems, from high-speed pipelines and multi-level caches to specialized Data Processing Units (DPUs) for networking and Tensor Streaming Processors (TSP) for AI acceleration. You’ll learn how to optimize hardware for massive parallelism, handle sophisticated memory hierarchies, and address real-world challenges in security, reliability, and energy efficiency. Through hands-on labs and real-world case studies, you’ll explore the very architectures shaping HPC, data centers, and AI—and gain the skills to help build tomorrow’s hardware breakthroughs.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
1. Hennessy, John L., and David A. Patterson. Computer Architecture: A Quantitative Approach (6th ed.) 2. Culler, David E., Jaswinder Pal Singh, and Anoop Gupta. Parallel Computer Architecture: A Hardware/Software Approach.
Additional Literature
1. Online resources 2. Tools and platforms: GEM5, SimpleScalar/Multi2Sim, GPGPU-Sim, P4/DPDK (Data Plane Development Kit), McPAT/CACTI, Linux perf / VTune ProfilerTeaching Methods
Interactive lectures with hands-on, project-based learning
Live demos and conceptual Q&A, student-led paper presentations
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction & advanced performance metrics | |
| 2 | Instruction-level parallelism (ILP) & advanced pipeline techniques | |
| 3 | Memory hierarchy & advanced caching | |
| 4 | Virtual memory & emerging memory technologies | |
| 5 | Shared-memory multiprocessors & multithreading | |
| 6 | Cache coherence protocols & memory consistency | |
| 7 | GPU architectures & tensor streaming processors (TSP) | |
| 8 | Mid-term | |
| 9 | Data processing units (DPUs) & SmartNICs (focus on pensando) | |
| 10 | Interconnection networks & on-chip networks, dataflow & warehouse-scale architectures | |
| 11 | Energy efficiency & thermal-aware design | |
| 12 | Reliability, Fault Tolerance & Security | |
| 13 | Domain-Specific & Emerging Architectures | |
| 14 | Project Presentations | |
| 15 | Final exam preparations & Course Synthesis |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| CS509.1 | Course | Tuesday 17:00 - 19:50 | A F1.4 - Class/Laboratory | - | - |
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Midterm
AI: Not AllowedAlignment with Learning Outcomes :
Course Project
AI: Not AllowedAlignment with Learning Outcomes :
Research Paper
AI: Not AllowedAlignment with Learning Outcomes :
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lectures
42 hours ⏳ (14 week × 3 h)
Research and Home study
60 hours ⏳ (10 week × 6 h)
Mid-term exam study
20 hours ⏳ (4 week × 5 h)
Final exam study
28 hours ⏳ (4 week × 7 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [CS509] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Oct 10, 2025 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| CS509 | Advanced Computer Architecture | 3 | 0 | 6 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Amal Mersni | Office Hours / Room / Phone | Tuesday: 14:00-16:00 Thursday: 9:00-11:00 , 13:00-14:00 (Internship consultations , internship application forms) |
|||||||
| amersni@ius.edu.ba | ||||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | This course dives deep into the design principles and performance breakthroughs powering today’s most innovative systems, from high-speed pipelines and multi-level caches to specialized Data Processing Units (DPUs) for networking and Tensor Streaming Processors (TSP) for AI acceleration. You’ll learn how to optimize hardware for massive parallelism, handle sophisticated memory hierarchies, and address real-world challenges in security, reliability, and energy efficiency. Through hands-on labs and real-world case studies, you’ll explore the very architectures shaping HPC, data centers, and AI—and gain the skills to help build tomorrow’s hardware breakthroughs. |
|||||||||
| Textbook | 1. Hennessy, John L., and David A. Patterson. Computer Architecture: A Quantitative Approach (6th ed.) 2. Culler, David E., Jaswinder Pal Singh, and Anoop Gupta. Parallel Computer Architecture: A Hardware/Software Approach. | |||||||||
| Additional Literature |
|
|||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Interactive lectures with hands-on, project-based learning. Live demos and conceptual Q&A, student-led paper presentations. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction & advanced performance metrics | |||||||||
| Week 2 | Instruction-level parallelism (ILP) & advanced pipeline techniques | |||||||||
| Week 3 | Memory hierarchy & advanced caching | |||||||||
| Week 4 | Virtual memory & emerging memory technologies | |||||||||
| Week 5 | Shared-memory multiprocessors & multithreading | |||||||||
| Week 6 | Cache coherence protocols & memory consistency | |||||||||
| Week 7 | GPU architectures & tensor streaming processors (TSP) | |||||||||
| Week 8 | Mid-term | |||||||||
| Week 9 | Data processing units (DPUs) & SmartNICs (focus on pensando) | |||||||||
| Week 10 | Interconnection networks & on-chip networks, dataflow & warehouse-scale architectures | |||||||||
| Week 11 | Energy efficiency & thermal-aware design | |||||||||
| Week 12 | Reliability, Fault Tolerance & Security | |||||||||
| Week 13 | Domain-Specific & Emerging Architectures | |||||||||
| Week 14 | Project Presentations | |||||||||
| Week 15 | Final exam preparations & Course Synthesis | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 30 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Midterm | 1 | 10 | Not Allowed | ||
| Course Project | 2 | 35 | Not Allowed | ||
| Research Paper | 1 | 25 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lectures | 3 | 14 | 42 | Research and Home study | 6 | 10 | 60 | |||
| Mid-term exam study | 5 | 4 | 20 | Final exam study | 7 | 4 | 28 | |||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 23/10/2025 | |||||||||