Shashank Prasanna
Docendo discimus (by teaching, we learn)
-Seneca
Hi! 👋🏽 Welcome! I’m a multi-disciplinary engineer and technology communicator. I find joy in creating science and technology education content. I write and talk about machine learning, specialized machine learning hardware (AI Accelerators), high-performance computing (HPC) and cloud computing and occasionally Physics and engineering.
I currently work at Modular AI educating developers how to accelerate AI and scientific applications using Mojo🔥 programming language and MAX Engine.
If this interests you, please reach out to me using my social media handles on the left navigation pane.
I regularly speak and conduct workshops at popular conferences. I’ve spoken at multiple editions of: NVIDIA GTC, O'Reilly AI, TensorFlow World, Open Data Science Conference (ODSC), Docker Community events, Future Technologies Conference (FTC), AWS Re:Invent, AWS Re:MARS, AWS Summits, Innovates and DevDays, Collision, AI accelerator conf., University events (UIUC, OSU) and others.
You can find some of my talk recordings below.
When I’m not writing, reading, video recording or spending time with my family, you will find me running 🏃 on local streets and trails. I try and test a lot of running shoes 👟 and read a lot of running related books. I also enjoy coffee brewing and coffee drinking even more ☕️.
Popular blog posts, video and conference talks
Choosing the right GPU for deep learning on AWS (🔥150k+ views)
A complete guide to AI accelerators for deep learning inference (🔥50k+ views)
AI accelerators, machine learning algorithms and their co-design and evolution
How Docker Runs Machine Learning on NVIDIA GPUs, AWS Inferentia, and Other Hardware AI Accelerators
Deploying GPU-Optimized Machine Learning Models to the Cloud and the Edge
TensorRT 3: Faster TensorFlow Inference and Volta Support
Production Deep Learning with NVIDIA GPU Inference Engine
Deep Learning for Computer Vision with MATLAB and cuDNN
Deep Learning for Object Detection with DIGITS
GTC: A Developer’s Guide to Choosing the Right GPUs for Deep Learning
GTC: A Developer’s Guide to Improving GPU Utilization and Reducing Deep Learning Costs
GTC: Improve ML Training Performance with Amazon SageMaker Debugger
Accelerating Data Science with NVIDIA RAPIDS on AWS
GTC: GPU-Accelerated Deep Learning at Scale with TensorFlow, PyTorch, and MXNet in the Cloud
Why use Docker containers for machine learning development?
Introducing Amazon SageMaker Components for Kubeflow Pipelines
A quick guide to distributed training with TensorFlow and Horovod
Choose the right instance for inference deployment with SageMaker Inference Recommender
Speeding up deep learning training with SageMaker Training Compiler
Introduction to Amazon SageMaker Serverless Inference | Concepts & Code examples
Get access to FREE GPU-powered JupyterLab based IDE for ML with Amazon SageMaker Studio Lab
Machine Learning with Containers and Amazon SageMaker
Machine Learning with Containers and Amazon SageMaker
Keynote: How machine learning is making customer experience more human
Using Containers for Deep Learning Workflows
Train Deep Learning Models on GPUs using Amazon EC2 Spot Instances (outdated approach)
How Pytorch 2.0 accelerates deep learning with operator fusion and CPU/GPU code-generation
Machine learning with AutoGluon, an open source AutoML library
Introduction to TorchServe, an open-source model serving library for PyTorch
Deploying PyTorch models for inference at scale using TorchServe
A quick guide to managing machine learning experiments
How to scale machine learning experiments
How to debug machine learning models to catch issues early and often
An easy introduction to Mojo🔥 for Python programmers
Implementing NumPy style matrix slicing in Mojo🔥
How to setup a Mojo🔥 development environment with Docker containers
Introduction to Tensors in Mojo🔥
Using the Mojo 🔥 Visual Studio Extension 🚀
Using Mojo🔥 with Docker containers
Getting started with the Mojo SDK🔥
Speeding up Python code with Mojo🔥: Mandelbrot example
🎥 Mojo🔥 livestreams
Modular Community Livestream – ModCon recap + Q&A
Modular Community Livestream - Mojo🔥 SDK v0.5 edition!
Modular Community Livestream - Mojo🔥 on Mac
Modular Community Livestream - Mojo🔥 SDK
Modular Community Livestream - 1st edition
🎥 PyTorch livestreams
PyTorch 2.0 Q&A: PyTorch 2.0 Export
PyTorch 2.0 Q&A: A Deep Dive on TorchDynamo
PyTorch 2.0 Q&A: Deep Dive into TorchInductor and PT2 Backend Integration
PyTorch 2.0 Q&A: Optimizing Transformers for Inference
PyTorch 2.0 Q&A: Dynamic Shapes and Calculating Maximum Batch Size
PyTorch 2.0 Q&A: TorchRL
PyTorch 2.0 Q&A: 2-D Parallelism using DistributedTensor and PyTorch DistributedTensor
🛠️ Workshop
A Tour of PyTorch 2.0
PyTorch Distributed Training on AWS
Key announcements from ModCon 2023
What’s new in Mojo SDK v0.5?
Mojo🔥 is now available on Mac
What’s the difference between the AI Engine and Mojo?
Modular to bring NVIDIA Accelerated Computing to the MAX Platform
Modular partners with Amazon Web Services (AWS) to bring MAX Enterprise Edition exclusively to AWS services
RAPIDS Accelerates Data Science End-to-End
7 things you should know about AI & Machine Learning launches at re:invent 2021
ModCon 2023 sessions you don’t want to miss!