AI Luminaries
A curated collection of videos featuring top experts in artificial intelligence.
Overview
Increasing complexity of machine learning (ML) algorithms have necessitated the emergence of specialized computer systems. Some ML algorithms are executed at edge, some are executed on the cloud. In this course, we will delve into different computing kernels of both training and inference of ML algorithms and see how they can be efficiently computed. Specifically, we will cover different system optimization techniques for convolutional neural network (CNN), large language models (LLMs) and Graph Neural Networks (GNNs).
Syllabus 10
- Week 1 Introduction
- Introduction to the course
- Neural Networks
- Introduction to Convolutional Neural Network - 1
- Introduction to Convolutional Neural Network - 2
- Convolutional Neural Network-1
- Week 2 Convolutional Neural Network
- Convolutional Neural Network-2
- Convolutional Neural Network-3
- Canonical CNN Architectures - 1
- Canonical CNN Architectures - 2
- CNN Computational Optimization Techniques
- Week 3 CNN Accelerators
- Dataflow for CNN Execution - 1
- Dataflow for CNN Execution - 2
- CNN Accelerators - 1
- CNN Accelerators 2
- CNN Accelerators 3
- Week 4 CNN Optimization
- CNN Accelerators 4
- CNN prunning - 1
- CNN pruning - 2
- Parallelism in CNN - 1
- Parallelism in CNN - 2
- Week 5 LLMs
- Parallelism in CNN - 3
- Parallelism in CNN - 4
- Parallelism in CNN - 5
- LLMs-1
- LLMs-2
- Week 6 LLMs
- LLMs-3
- LLMs-4
- LLMs-5
- LLMs-6
- LLMs-7
- Week 7 LLMs
- LLMs-8
- LLMs-9
- LLMs-10
- Distributed Service
- Fault Tolerance
- Week 8 Model Checkpointng
- Fault-Tolerant Training
- Fundamentals of Graph Neural Networks-1
- Fundamentals of Graph Neural Networks-2
- Hardware Acceleration of Graph Neural Networks-1
- Hardware Acceleration of Graph Neural Networks -2
- Week 9 In-Memory Computing(IMC)
- ISSAC, Pipelayer
- Pipelayer[contd.], Atomlayer, Simulation platform
- Simulation platform, Area-aware optimization, communication-aware optimization
- Communication-Aware optimization, Achieving minimum communication latency
- Achieving minimum communication latency
- Week 10 GNN Accelerator
- Advanced Hardware Architectures for GNN Acceleration
- Communication-Aware Pruning for IMC
- Re-Transformer
- Performance Evaluation of 2.5D IMC-Based AI Accelerators
- Chiplet-Based Heterogeneous Architectures for LLM Acceleration
Advantages and disadvantages
Advantages
- Taught by IIT and IISc professors, and it follows the Indian university syllabus closely.
- All videos and assignments are free on NPTEL and SWAYAM.
- The certificate is recognised by many Indian universities for credit transfer and by GATE aspirants.
- Great for GATE and semester exam preparation.
- Taught by Indian Institute of Science, one of the strongest names in its field.
- Completely free.
- Self-paced: start any time.
- A clear syllabus (10 parts) you can see before you start.
Disadvantages
- The certificate needs a proctored exam at a centre, which has a fee.
- Recorded classroom lectures: thorough, but slower than made-for-online courses.
- New runs start on fixed dates (January and July).
- Learning is free, but the certificate costs money.
Some points apply to every course of this kind; see how we rank.
Free to learn
- Free: Every video and assignment is free on NPTEL and SWAYAM. Enrol when the next run opens.
- Certificate: Optional. It needs a proctored exam at a centre, which has a fee.
Before you start
Computer Organization
Taught by
- Prof. Sumit K. MandalIISc Bangalore
Indian Institute of Science is in Tier 1: world-leading universities and India's top institutes of our institution ranking (96/100).
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