Documentation

SCAILIUME Docs

Everything you need to integrate, configure, and optimize SCAILIUME for your AI infrastructure.

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Getting Started

Quick start guides and tutorials to get you up and running with SCAILIUME.

API Reference

Complete API documentation for all SCAILIUME interfaces and endpoints.

Data Integration

Connect SCAILIUME to your existing data sources and storage systems.

GPU Configuration

Optimize your GPU clusters for maximum throughput with SCAILIUME.

Configuration

Advanced configuration options and environment settings.

Security

Security best practices and compliance documentation.

Quick Start Example

pipeline.py
import scailiume as sc

# Initialize the GPU-native pipeline
pipeline = sc.Pipeline(
    source="s3://your-bucket/data",
    gpu_cluster="cuda:0,1,2,3",
    batch_size=1024
)

# Configure zero-copy data streaming
pipeline.configure(
    zero_copy=True,
    prefetch_batches=4,
    compression="lz4"
)

# Run inference with continuous data supply
for batch in pipeline.stream():
    predictions = model.predict(batch)
    results.append(predictions)

# Monitor GPU utilization
print(f"GPU Utilization: {pipeline.metrics.utilization}%")
print(f"Throughput: {pipeline.metrics.throughput} samples/sec")

Need Help?

Our engineering team is here to help you get the most out of SCAILIUME.