SeaWulf is a heterogeneous cluster with over 400 nodes and 23,000 cores, designed to provide a range of computational resources for different research needs.
Hardware Generations and Access
SeaWulf's hardware spans multiple generations, accessible via different login nodes:
Legacy Platform (login1/login2)
The original SeaWulf hardware:
- Haswell 28-core nodes: Mature, stable platform with AVX2 support
- GPU acceleration: K80, P100, and V100 GPUs for older CUDA applications
- Best for: Legacy software, budget-conscious computing, development work
Modern Platform (milan1/milan2)
Expanded infrastructure with newer hardware:
- Multiple CPU architectures: Intel Skylake, AMD Milan, Intel Sapphire Rapids
- Memory innovations: Standard DDR5, high-bandwidth HBM, and massive 1TB configurations
- GPUs: NVIDIA A100 GPUs for more demanding CUDA applications
- Specialized features: Shared access modes, high memory bandwidth
Note: Your login node choice determines available resources. See the SeaWulf Queue Table for a direct comparison.
Understanding Performance Characteristics
CPU Architecture Differences
Different CPU generations have distinct performance profiles:
| Architecture | Strengths | Ideal Applications |
|---|---|---|
| Intel Haswell (28-core) | Stable, widely compatible | Legacy codes, development, general computing |
| Intel Skylake (40-core) | Balanced performance, modern instruction sets | Most scientific computing workloads |
| AMD Milan (96-core) | High parallelism | Highly parallel applications, parameter sweeps |
| Intel Sapphire Rapids (96-core) | Advanced instruction sets, HBM memory | AI/ML inference, memory-intensive applications |
Memory
- Standard DDR5: Balanced performance for most applications
- High-Bandwidth Memory (HBM): Better for memory bandwidth-limited applications. For more information see HBM Nodes.
- Large-memory nodes: Useful for in-memory processing of very large datasets
Shared vs Dedicated Access
SeaWulf through shared access modes:
Dedicated Access
- Your job gets exclusive access to entire nodes
- Guaranteed resources and performance
- Best for large, resource-intensive applications
- Higher resource cost per computation
Shared Access
- Multiple users can run jobs on the same node
- More efficient utilization of system resources
- Ideal for smaller jobs that don't need full nodes
- Faster queue times, lower resource cost
System Scalability
Supports a range of workloads:
- Single-core tasks
- Multi-threaded single-node jobs (up to 96 cores)
- Multi-node distributed applications
The scheduling system automatically handles resource allocation and job placement, optimizing performance while maintaining fair access across all users.
Scaling Tip: Not all applications benefit from using more resources; use available tools to find optimal allocations.