Overall Architecture Philosophy

SeaWulf is built on a distributed computing model that combines high-performance processors, specialized accelerators, and ultra-fast networking into a cohesive computational ecosystem. The cluster consists of over 400 nodes and approximately 23,000 cores, delivering a peak performance of around 1.86 PFLOP/s for research computations.

The architecture follows industry best practices for HPC cluster design, emphasizing scalability, fault tolerance, and efficient resource utilization. SeaWulf uses top-of-the-line components from Penguin, DDN, Intel, Nvidia, Mellanox, and numerous other technology partners, creating a heterogeneous environment optimized for different computational paradigms.

System Topology

Hierarchical Structure

SeaWulf employs a hierarchical cluster topology consisting of multiple layers:

Network Topology

The nodes are interconnected via high-speed InfiniBand (IB) networks by Nvidia, enabling data transfer speeds ranging from 5 to 50 gigabytes per second. The network employs a switched fabric architecture that provides:

• Low Latency Communication: InfiniBand uses a switched fabric topology with point-to-point channels, minimizing communication delays
• High Bandwidth: Multiple parallel pathways for data transmission
• Fault Tolerance: Redundant connections and automatic failover capabilities
• Scalability: Ability to expand the network as new nodes are added

Node Architecture

Heterogeneous Computing Environment

SeaWulf's strength lies in its heterogeneous node architecture, featuring different types of compute nodes optimized for specific workloads. The cluster is organized across multiple generations of hardware platforms accessible through different login node groups.

Legacy Haswell Generation (login1/login2 access)

• 128 GB memory per node for balanced workloads
• AVX2 vector processing capabilities
• Mature, stable platform for production workloads
• GPU variants with 4x K80 24GB GPUs for acceleration
• Specialized GPU nodes with P100 (16GB) and V100 (32GB) accelerators

Modern Skylake Generation (milan1/milan2 access)

• 192 GB memory per node with improved bandwidth
• AVX512 vector processing for enhanced computational throughput
• Both dedicated and shared-access configurations available
• Optimized for modern HPC workloads requiring higher memory capacity

High-Density AMD Milan Generation

• 256 GB memory per node supporting memory-intensive applications
• AVX2 vector processing optimized for AMD architecture
• Exceptional parallel processing capability with 96 cores per node
• Available in both dedicated and shared-access modes
• Ideal for embarrassingly parallel problems and large-scale simulations

Next-Generation HBM Nodes

• 384 GB total memory (256GB DDR5 + 128GB HBM) for standard HBM nodes
• Specialized 1TB nodes with DDR5 memory and HBM configured as L4 cache
• AMX, AVX512, and Intel DL Boost instruction sets
• Revolutionary memory architecture delivering 2-4x performance improvements
• Optimized for memory-bound and AI/ML workloads

Modern GPU Acceleration Platform

• 4x NVIDIA A100 80GB GPUs per node
• 64 Intel Ice Lake cores with AVX512 and Intel DL Boost
• 256 GB system memory supporting large-scale GPU computations
• Multi-user shared access capability for efficient resource utilization
• Optimized for AI/ML training and high-performance scientific computing

Storage Architecture

Parallel File System

SeaWulf employs a GPFS (General Parallel File System) architecture that provides:

• Concurrent Access: Multiple nodes can simultaneously access the same files
• High Throughput: Aggregated bandwidth from multiple storage devices
• Fault Tolerance: Data redundancy and automatic failover
• Scalability: Storage capacity and performance scale with system growth

Storage Hierarchy

Access Architecture

Dual Login Node System

SeaWulf employs a sophisticated access architecture featuring two distinct login node clusters that provide access to different hardware generations:

Queue Organization

The cluster's queue system is organized by computational requirements and hardware capabilities:

• Debug Queues: Short-duration testing and development work
• Short/Medium/Long Queues: Production workloads with varying time requirements
• Extended Queues: Long-running computations up to 7 days
• Large Queues: High-throughput parallel jobs requiring many nodes
• Shared Queues: Efficient resource utilization allowing multiple users per node
• Specialized Queues: GPU acceleration and HBM memory optimization

Scalability and Future Growth

Modular Design

SeaWulf's architecture is designed for growth and adaptation:

• Incremental Expansion: New nodes can be added without disrupting existing operations
• Technology Refresh: Individual components can be upgraded independently
• Workload Adaptation: Node types can be reconfigured for changing research needs
• Network Growth: InfiniBand fabric supports additional connections

Performance Optimization

The architecture incorporates several optimization strategies:

• Workload Placement: Automatic job placement on optimal node types
• Network Optimization: Traffic engineering for minimal congestion
• Resource Balancing: Dynamic load distribution across available resources
• Energy Efficiency: Power management features to optimize energy consumption

Architectural Advantages

SeaWulf's sophisticated architecture delivers several key advantages for high-performance computing:

Performance Benefits

• Computational Diversity: Multiple node types optimize different workload categories
• High-Speed Communication: InfiniBand provides industry-leading interconnect performance
• Memory Innovation: HBM technology delivers breakthrough memory performance
• Accelerated Computing: GPU integration supports emerging computational paradigms

Operational Excellence

• Resource Efficiency: Intelligent scheduling maximizes utilization
• Fault Resilience: Redundant systems ensure high availability
• Management Simplicity: Centralized administration and monitoring
• User Accessibility: Multiple access methods and interfaces