High-Performance Deep Learning Training

Hai-Platform provides task-level GPU time-sharing scheduling for optimal resource utilization and faster model training.

Current GPU Utilization

87%

Advanced GPU Time-Sharing Technology

Optimize your deep learning workflows with our innovative scheduling system

Task-Level Scheduling

Precise GPU time allocation at the task level for maximum efficiency and minimal idle time.

High Utilization

Achieve up to 95% GPU utilization with our intelligent resource allocation algorithms.

Multi-Tenancy

Run multiple training jobs simultaneously on the same GPU cluster without interference.

GPU Cluster Dashboard

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Node-1

NVIDIA A100 80GB

Active
GPU Utilization 78%
Memory Usage 64GB / 80GB

Running Jobs:

ResNet-50 Training
BERT Fine-tuning

Node-2

NVIDIA V100 32GB

Active
GPU Utilization 92%
Memory Usage 28GB / 32GB

Running Jobs:

YOLOv5 Object Detection
GAN Training

Node-3

NVIDIA A40 48GB

Pending
GPU Utilization 15%
Memory Usage 8GB / 48GB

Queued Jobs:

Transformer Pre-training

Submit New Training Job

Configure your deep learning training job with our advanced scheduling options to maximize GPU utilization.

Time-Sharing Benefits

  • Reduced training time through optimized GPU sharing
  • Lower costs with efficient resource allocation
  • Priority scheduling for critical jobs
minutes

Recommended: 30-60 minutes for optimal scheduling

Cluster Performance Metrics

GPU Utilization Over Time

GPU Utilization Chart

Job Completion Times

Job Performance Chart

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