Statements (69)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:lighthouse
|
| gptkbp:bfsLayer |
4
|
| gptkbp:bfsParent |
gptkb:Py_Torch
|
| gptkbp:based_on |
gptkb:operating_system
|
| gptkbp:can_be_used_with |
gptkb:Torch_Script
Mixed Precision Training |
| gptkbp:enables |
Model Parallelism
|
| https://www.w3.org/2000/01/rdf-schema#label |
Distributed Data Parallel
|
| gptkbp:improves |
Training Speed
|
| gptkbp:is_adopted_by |
Startups
Tech Companies |
| gptkbp:is_available_on |
gptkb:Py_Torch_1.0
|
| gptkbp:is_compatible_with |
gptkb:board_game
gptkb:CUDA Various Operating Systems |
| gptkbp:is_designed_for |
Distributed Training
|
| gptkbp:is_documented_in |
Technical Blogs
Git Hub Repositories Py Torch Documentation |
| gptkbp:is_enhanced_by |
Profiling Tools
Data Parallelism Techniques Performance Tuning Techniques NCCL (NVIDIA Collective Communications Library) |
| gptkbp:is_evaluated_by |
Research Papers
Benchmarking Studies |
| gptkbp:is_implemented_in |
gptkb:Torch_Distributed
gptkb:Library |
| gptkbp:is_integrated_with |
gptkb:fortification
Other Libraries CI/ CD Pipelines |
| gptkbp:is_optimized_for |
Large Scale Models
Multi-node Training |
| gptkbp:is_part_of |
gptkb:Py_Torch_Framework
High-Performance Computing AI Frameworks AI Research Labs Deep Learning Ecosystem |
| gptkbp:is_supported_by |
gptkb:software_framework
Community Contributions Cloud Platforms NVIDIAGP Us Hardware Accelerators |
| gptkbp:is_tested_for |
Real-Time Applications
Real-World Scenarios Various Benchmarks Synthetic Datasets |
| gptkbp:is_used_for |
gptkb:Research_Institute
Collaborative Research Neural Network Training |
| gptkbp:is_used_in |
Industry Applications
Deep Learning Research Production Environments |
| gptkbp:is_utilized_in |
Model Training
AI Competitions AI Researchers Scalable AI Solutions High-Throughput Training |
| gptkbp:managed_by |
Distributed Sampler
|
| gptkbp:provides |
Automatic Gradient Averaging
|
| gptkbp:reduces |
Gradient Synchronization Time
|
| gptkbp:requires |
Multiple GP Us
Distributed Environment |
| gptkbp:scales |
Thousands of GP Us
|
| gptkbp:setting |
Resource Management
Fault Tolerance Environment Variables |
| gptkbp:suitable_for |
Large Datasets
Data Parallel |
| gptkbp:supports |
Data Parallelism
|