Load Balancing Strategy

The Mathematical Art of Ensuring Computational Equality.

HPC Load Balancing: Beyond Web Servers

In a standard web server, load balancing means sending User A to Server 1 and User B to Server 2. In HPC, load balancing happens inside a single simulation running on 1,000+ cores. If you split a car crash simulation into 1,000 pieces, but the "crash" only occurs in piece #5, that one core does all the work while the other 999 sit idle. Our goal: Every core finishes at the exact same millisecond.

Static Load Balancing (The Pizza Slicer)

Workload is divided evenly before the simulation starts (e.g., a 100x100 grid split into 4 equal quarters).

  • Zero overhead during execution.
  • Fails on "irregular" problems (e.g., explosions in one corner).

Dynamic Load Balancing (The Buffet)

Workload is redistributed during the simulation as the physics evolve (turbulence, fire, impacts).

  • Handles unpredictable physics perfectly.
  • High communication overhead; moving data takes time.

Advanced Balancing Algorithms

Work Stealing: The Gold Standard

When a processor becomes idle, it "steals" tasks from the back of a busy processor's queue. This decentralized approach removes the "Master Node" bottleneck.

Domain Decomposition (Graph Partitioning)

Using METIS/ParMETIS to cut 3D meshes into chunks with equal weight but minimal surface area to reduce network traffic between nodes.

Cluster-Level Balancing (Slurm GRES)

Beyond the code, the scheduler balances hardware currencies (CPUs, GPUs, RAM). We configure Generic Resources (GRES) to ensure jobs are matched to the specific hardware they need without wasting specialized nodes.

  • Tracking "Currencies": GPU vs. High-RAM.
  • Multifactor Priority (Age, Fairshare).
  • Optimized Resource Backfilling.

Load Balancing Toolkit

Category Tool Usage
Graph Partitioning METIS / ParMETIS Slicing 3D meshes into equal-weight chunks for MPI.
Dynamic Runtime Charm++ Automatically moves objects between cores 100x/sec.
Code Library Zoltan Sandia National Labs toolkit for dynamic data management.
Scheduler Slurm (Multifactor) Balances queue priority to keep cluster utilization at 100%.

Eliminate Idle Cycles

Download our "Parallel Efficiency Guide" to learn how to identify load imbalance in your MPI applications.

Download Efficiency Guide (.docx)