CORE

High Performance Computing

24CSE685 · S6 · 4 credits

Official KTU 2024 syllabus subject — study with practice, PYQs and AI tools.

§
Syllabus
Loading syllabus…
Manage →
⚡ DAY-BEFORE EXAM

Have an exam tomorrow?

Get a high-yield attack plan focused on maximum marks per minute. Zero fluff, strict PYQ priority, active recall, and trap avoidance.

Strategy: High-yield concepts + PYQs + weak areas

Tap a module to mark as weak
PRIORITY A
Module 1

Why:Foundation module

+ Mark Weak
PRIORITY A
Module 2

Why:High exam relevance

+ Mark Weak
PRIORITY B
Module 3

Why:Core module

+ Mark Weak
PRIORITY B
Module 4

Why:Applied concepts

+ Mark Weak
PRIORITY C
Module 5

Why:Standard exam coverage

+ Mark Weak
Modules
Module 01Modern Processors (8 hours)expand

Stored-program computer architecture, Need for Parallelism, Data parallelism, Functional parallelism. Parallel Computers- SIMD systems, MIMD systems. Parallel architectures- superscalar architectures, multi-core, multi-threaded, server and cloud.

Module 02Navigating the High-Performance Computing Landscapeexpand

(7hours) Importance of HPC in current times, Fundamental design issues in HPC- Load balancing, Scheduling, Synchronization and Resource management. Operating systems for scalable HPC. Fundamental limitations in HPC- bandwidth, latency and latency hiding techniques. Benchmarking HPC

Module 03Shared-memory parallel programming with OpenMP (7 hours)expand

Parallel execution, Data scoping, OpenMP work-sharing for loops, Synchronization, Reductions, Loop scheduling, Tasking, Cache Coherence, and False Sharing- Thread Safety. Case study: OpenMP-parallel Jacobi algorithm.

Module 04Distributed-memory parallel programming with MPI (6 hours)expand

Message passing, Messages and point-to-point communication, The Trapezoidal Rule in MPI, Collective communication, Nonblocking point-to-point, Virtual topologies, A Parallel Sorting Algorithm- Odd even Transposition Sort.

Module 05Advanced Topics (8 hours)expand

Accelerated HPC- architecture, programming and typical accelerated system with GPU, FPGA and Xeon Phi. Handling big data- Introduction to HDF5. Visualization tools- VisIt and Paraview. Peta scale computing, optics in HPC, quantum computers.

Notes / Resources

Exam-focused notes are optional context — Continue Learning above works even without them.

Notes for this subject aren't written yet

Continue Learning above adapts to this subject anyway — it teaches from your active syllabus.