AI Infra HandbookContact ↗Contact ↗ (opens in a new tab)
GitHubGitHub (opens in a new tab)
  • Introduction
  • Building Blocks
    • Compute Architecture
      • GPU Architecture Overview
      • CPU vs GPU Computing
      • Tensor Cores
      • CUDA Cores
      • NVIDIA A100 Architecture
      • NVIDIA H100 Architecture
      • Google TPU Architecture
      • Numerical Precision
      • GPU Driver Stack
      • Host CPU Systems
    • Memory Systems
      • Memory Hierarchy
      • High Bandwidth Memory (HBM)
      • System Memory (DRAM)
      • Cache Architecture
      • Memory Bandwidth
      • Cache Coherency
    • Interconnects
      • Network Topology
      • NVIDIA NVLink
      • PCIe Interface
      • InfiniBand
      • RDMA Technology
      • Ethernet Networks
    • Storage Systems
      • Storage Technologies
      • Parallel File Systems
      • Distributed Storage
      • GPUDirect Storage
      • I/O Patterns
      • Data Pipeline Optimization
    • Power & Cooling
      • Power Consumption
      • Power Infrastructure
      • Power Delivery
      • Cooling Systems
      • Power Usage Effectiveness
      • Heat Density Management
    • Understanding Performance
      • Computing Performance (FLOPS)
      • System Bandwidth
      • System Latency
      • System Throughput
      • Resource Utilization
      • Energy Efficiency
      • Benchmarking
    • Parallel Processing
      • Distributed Training Overview
      • Model Parallelism
      • Data Parallelism
      • Pipeline Parallelism
    • Software Stack
      • AI Frameworks
        • PyTorch
        • TensorFlow
      • Parallel Computing
        • Message Passing Interface (MPI)
        • NVIDIA NCCL
        • OpenMP
      • Virtualization
        • Containers
        • GPU Virtualization
      • CUDA Programming
      • Operating Systems
      • Orchestration
  • Single Node Systems
    • DGX A100 Architecture
    • DGX H100 Architecture
    • NVLink Topology
    • NVSwitch Architecture
    • Node Optimization
  • Multi-Node Architecture
    • DGX POD Architecture
      • POD Architecture
      • POD Networking
      • Storage Architecture
      • POD Management
    • Multi-Pod Scaling
      • Network Architecture
      • Storage Architecture
      • Power & Cooling
  • Training at Scale
    • System Architecture
      • Model Distribution
      • Data Parallelism
      • Communication Patterns
    • Data Management
      • Data Pipeline
      • Storage Hierarchy
      • I/O Optimization
    • Performance
      • Bottleneck Analysis
      • GPU Utilization
      • Network Optimization
      • Memory Management
    • Scaling Strategies
      • Cluster Scaling
      • Efficiency Metrics
      • Debugging
  • Operations & Management
    • Deployment
      • Cluster Setup
      • Network Setup
      • Storage Setup
    • Monitoring
      • System Metrics
      • Training Metrics
      • Alerting
    • Maintenance
      • System Updates
      • Troubleshooting
      • Backup & Recovery
    • Optimization
      • Power Management
      • Cost Optimization
      • Performance Tuning
  • Commercial Systems
    • NVIDIA Systems
      • Selene Supercomputer
      • DGX SuperPOD
    • Google Infrastructure
      • TPU v4 Pod
    • Meta Infrastructure
      • Research SuperCluster
  • Introduction
  • Building Blocks
    • Compute Architecture
      • GPU Architecture Overview
      • CPU vs GPU Computing
      • Tensor Cores
      • CUDA Cores
      • NVIDIA A100 Architecture
      • NVIDIA H100 Architecture
      • Google TPU Architecture
      • Numerical Precision
      • GPU Driver Stack
      • Host CPU Systems
    • Memory Systems
      • Memory Hierarchy
      • High Bandwidth Memory (HBM)
      • System Memory (DRAM)
      • Cache Architecture
      • Memory Bandwidth
      • Cache Coherency
    • Interconnects
      • Network Topology
      • NVIDIA NVLink
      • PCIe Interface
      • InfiniBand
      • RDMA Technology
      • Ethernet Networks
    • Storage Systems
      • Storage Technologies
      • Parallel File Systems
      • Distributed Storage
      • GPUDirect Storage
      • I/O Patterns
      • Data Pipeline Optimization
    • Power & Cooling
      • Power Consumption
      • Power Infrastructure
      • Power Delivery
      • Cooling Systems
      • Power Usage Effectiveness
      • Heat Density Management
    • Understanding Performance
      • Computing Performance (FLOPS)
      • System Bandwidth
      • System Latency
      • System Throughput
      • Resource Utilization
      • Energy Efficiency
      • Benchmarking
    • Parallel Processing
      • Distributed Training Overview
      • Model Parallelism
      • Data Parallelism
      • Pipeline Parallelism
    • Software Stack
      • AI Frameworks
        • PyTorch
        • TensorFlow
      • Parallel Computing
        • Message Passing Interface (MPI)
        • NVIDIA NCCL
        • OpenMP
      • Virtualization
        • Containers
        • GPU Virtualization
      • CUDA Programming
      • Operating Systems
      • Orchestration
  • Single Node Systems
    • DGX A100 Architecture
    • DGX H100 Architecture
    • NVLink Topology
    • NVSwitch Architecture
    • Node Optimization
  • Multi-Node Architecture
    • DGX POD Architecture
      • POD Architecture
      • POD Networking
      • Storage Architecture
      • POD Management
    • Multi-Pod Scaling
      • Network Architecture
      • Storage Architecture
      • Power & Cooling
  • Training at Scale
    • System Architecture
      • Model Distribution
      • Data Parallelism
      • Communication Patterns
    • Data Management
      • Data Pipeline
      • Storage Hierarchy
      • I/O Optimization
    • Performance
      • Bottleneck Analysis
      • GPU Utilization
      • Network Optimization
      • Memory Management
    • Scaling Strategies
      • Cluster Scaling
      • Efficiency Metrics
      • Debugging
  • Operations & Management
    • Deployment
      • Cluster Setup
      • Network Setup
      • Storage Setup
    • Monitoring
      • System Metrics
      • Training Metrics
      • Alerting
    • Maintenance
      • System Updates
      • Troubleshooting
      • Backup & Recovery
    • Optimization
      • Power Management
      • Cost Optimization
      • Performance Tuning
  • Commercial Systems
    • NVIDIA Systems
      • Selene Supercomputer
      • DGX SuperPOD
    • Google Infrastructure
      • TPU v4 Pod
    • Meta Infrastructure
      • Research SuperCluster
  • Contact ↗ (opens in a new tab)
Question? Give us feedback → (opens in a new tab)Edit this page
Training at Scale
Performance
Memory Management

Work in Progress. Will be updated soon...

Network OptimizationCluster Scaling
Open Source under the MIT License