Exploiting Parallelism in Large Scale Deep Learning Model Training: Chips to Systems to Algorithms Published 2022-05-10 Download video MP4 360p Download video MP4 720p Recommendations 58:07 Aligning LLMs with Direct Preference Optimization 56:39 Alpa: Automating Inter- and Intra- Operator Parallelism for Distributed Deep Learning 18:17 Can we reach AGI with just LLMs? 58:25 Singularity Containers 31:55 ABSOLUTELY INSANE CHESS!!!!! 32:50 Undefined Behavior in C++: What Every Programmer Should Know and Fear - Fedor Pikus - CppCon 2023 18:07 Graph neural networks: Variations and applications 59:04 Pavex: re-imaging what API development looks like in Rust - Luca Palmieri 1:33:08 Robots Are After Your Job: Exploring Generative AI for C++ - Andrei Alexandrescu - CppCon 2023 22:09 UK Slips Into Recession, London Loses Another Listing: Bloomberg UK Show 2:08:36 L4 Latent Variable Models and Variational AutoEncoders -- CS294-158 SP24 Deep Unsupervised Learning 1:12:00 BigScience BLOOM | 3D Parallelism Explained | Large Language Models | ML Coding Series 1:39:25 Hare Programming Language 57:58 Intermediate Linux 1:54:27 COMP2521 24T1 — Lecture 1: Week 1, Tuesday 1:08:07 Inside OpenAI | Logan Kilpatrick (head of developer relations) 1:06:53 [REFAI Seminar 03/30/23] Efficient Trillion Parameter Scale Training and Inference with DeepSpeed 31:16 Coroutine Patterns: Problems and Solutions Using Coroutines in a Modern Codebase - Francesco Zoffoli 1:18:40 S2024 #06 - Vectorized Query Execution Using SIMD (CMU Advanced Database Systems) 29:01 Powered by AI: A Cambrian Explosion for C++ Software Development Tools - Emery Berger - CppCon 2023 Similar videos 58:32 Exploiting Parallelism in Large Scale DL Model Training: From Chips to Systems to Algorithms 14:18 USENIX ATC '21 - ZeRO-Offload: Democratizing Billion-Scale Model Training 2:04:21 Tutorial: High-Performance Hardware for Machine Learning 23:39 Michio Kaku Breaks in Tears "Quantum Computer Just Shut Down After It Revealed This" 24:26 nVidia GTC'17: Building Brains - Parallelisation Strategies of large scale deep learning networks 1:19:06 Hardware-aware Algorithms for Sequence Modeling - Tri Dao | Stanford MLSys #87 37:36 RAS: Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM - G. Perrotta 27:54 tinyML Summit 2022: Mastering the 3 Pillars of AI Acceleration: Algorithms, Hardware and Software 1:05:36 David Patterson: A Decade of Machine Learning Accelerators:Lessons Learned and Carbon Footprint 20:59 8 SwitchML Scaling Distributed Machine Learning with In Network Aggregation 20:21 An Oracle for Guiding Large Scale Model:Hybrid Parallel Training of Convolutional Neural Networks 1:01:45 Practical Talk: Exploiting Structure for More Efficient NLP (Sasha Rush) 1:28:26 Research Session 7: Mining Time Series and Spatial Data 27:18 OSDI '14 - Project Adam: Building an Efficient and Scalable Deep Learning Training System 56:24 General Purpose, Low Power Supercomputing Using... 46:42 Bridging the Divide (...) - Christopher Brown, Kevin Hammond 1:42:51 Lec. 5 - Multi-Core Processors II - Carnegie Mellon - Parallel Computer Arch. 2012 - Onur Mutlu 56:24 General Purpose, Low Power Supercomputing Using Reconfiguration More results