Benchmarks

Benchmarks#

Benchmarks were conducted using Google Cloud’s Compute Engine with the following specifications:

Machine Configuration#

  • Machine Type: a2-highgpu-1g (vCPU count: 12, VM memory: 85 GB)

  • CPU Platform: Intel Cascade Lake

  • GPU: 1 x NVIDIA A100 40GB

  • Boot Disk: 250 GB SSD

Benchmark Setup#

  • Algorithm: FedAvg

  • Dataset: CIFAR-10

  • Number of Clients: 100

  • Communication Rounds: 5

  • Local Training: 5 epochs, Learning Rate: 0.1, Batch Size: 50

  • Role: - Server: Aggregation - Clients: Training and Evaluation (80% training, 20% evaluation)

  • Models: - CNN (size: 0.24 MB) - ResNet18 (size: 44.59 MB)

For benchmarking purposes, we utilized Flower’s Quickstart Example as a baseline to evaluate BlazeFL’s performance and efficiency.

CNN Benchmark ResNet18 Benchmark