MTech 1st Semester Syllabus (2024)

Unit 1: Introduction to Advanced Processor Design:

• Pipelining concepts, instruction-level parallelism (ILP) techniques (branch prediction, instruction scheduling, data forwarding), superscalar architecture.
• Performance metrics and analysis, Amdahl's Law, MIPS equation.

Unit 2: Memory Hierarchy and Cache Design:

• Cache organization (direct mapped, set associative, fully associative), cache coherence protocols (MESI, MSI), cache replacement policies (LRU, FIFO, Random).
• Virtual memory concepts, address translation (TLB, page table).

Unit 3: Parallel Computing Architectures:

• Multicore processors, shared memory vs. message passing architectures.
• Multiprocessors, clusters, grid computing, high-performance computing (HPC) systems.
• Introduction to vector processing and GPUs.

Unit 4: Performance Analysis and Optimization:

• Benchmarking methodologies and tools, performance metrics (throughput, latency, utilization).
• Profiling techniques, code optimization strategies.
• Introduction to parallel programming concepts."

• "Computer Architecture: A Quantitative Approach" by John L. Hennessy & David A. Patterson

• "Parallel Computing: Theory and Practice" by Michael J. Quinn

• "Advanced Processor Design for Superscalar and Chip-Multiprocessor Architectures" by David A. Patterson & John L. Hennessy

Unit 1: Advanced Process Management:

• Scheduling algorithms (multi-level queue scheduling, priority scheduling, real-time scheduling).
• Thread management, concurrency control mechanisms (mutexes, semaphores).
• Deadlock prevention and recovery techniques.

Unit 2: Advanced Memory Management:

• Virtual memory concepts, paging and segmentation techniques.
• Address translation (page table, TLB), memory protection mechanisms.
• Demand paging, working set model, thrashing.

Unit 3: Advanced File Systems:

• File system design principles, directory structures (inode, extent-based).
• Disk scheduling algorithms (FCFS, SCAN, C-SCAN).
• RAID concepts for data redundancy and performance.
• Journaling file systems for data integrity.

Unit 4: Virtualization and Containerization:

• Hypervisors and their types.
• Containerization concepts, Docker and Kubernetes.
• Security considerations in virtualization and containerization.

• "Operating Systems: Three Easy Pieces" by Remzi H. Arpaci-Dusseau & Andrea C. Arpaci-Dusseau

• "Advanced Operating Systems and Middleware" by Mukesh Singhal & Niran Jayakumar

• "The Linux Kernel Module Programming Guide" by Peter Membrey"

Unit 1: Advanced Sorting and Searching Algorithms:

• Heapsort, Quicksort, Mergesort, Radix Sort time and space complexity analysis.
• B-Search, Interpolation Search, their advantages and applications.

Unit 2: Advanced Graph Algorithms:

• Dijkstra's algorithm for shortest paths, Bellman-Ford algorithm for negative weights.
• Minimum spanning trees (Prim's algorithm, Kruskal's algorithm).
• Network flow algorithms (Ford-Fulkerson, Max-Flow Min-Cut).

Unit 3: Dynamic Programming:

• Dynamic programming principles and applications (Longest Common Subsequence, Matrix Chain Multiplication, Knapsack Problem).
• Memoization and tabulation techniques.

Unit 4: Advanced Data Structures:

• Tries for efficient prefix searches and auto-completion.
• B-Trees and their variations for efficient indexing and searching in large datasets.
• Skip Lists for probabilistic search with guaranteed worst-case performance.
• Self-balancing trees (AVL trees, Red-Black trees) for efficient insertions and deletions."

• "Introduction to Algorithms" by Thomas H. Cormen et al.

• "Algorithms on Graphs" by Vijay Vazirani

• "Data Structures and Algorithm Analysis in C++" by Michael T. Goodrich et al.

Unit 1: Advanced Database Design:

• Third Normal Form (3NF), Boyce-Codd Normal Form (BCNF) for data normalization and reducing redundancy.
• Denormalization techniques for performance optimization when appropriate.
• Entity-Relationship (ER) modeling for conceptual database design.

Unit 2: Advanced Query Optimization:

• Cost estimation for different query plans, join algorithms (nested loop, merge-join, hash-join).
• Indexing techniques (B+ trees, hash indexes) and their impact on query performance.
• Query optimization strategies like using appropriate indexes, exploiting selectivities.

Unit 3: Concurrency Control and Recovery:

• Locking mechanisms (optimistic locking, pessimistic locking) for concurrent access control.
• Transaction isolation levels (ACID properties) and their implications.
• Deadlock detection and recovery techniques.
• Recovery from crashes and transaction rollback mechanisms.

Unit 4: Distributed Database Systems:

• Distributed database architectures (client-server, peer-to-peer)
• Data replication techniques and consistency models
• Distributed query processing and optimization
• Transaction management in distributed systems
• Fault tolerance and recovery mechanisms
• Scalability and performance considerations in distributed databases"

• "Database System Concepts and Design" by Silberschatz, Korth, & Sudarshan

• "Transaction Processing: Concepts and Techniques" by Jim Gray & Andreas Reuter

• "Distributed Database Systems" by Stefano Ceri & Giuseppe Pelagatti