Definition
In AI engineering, throughput is a critical performance metric indicating system capacity. It is often measured in tokens per second for LLMs, images per second for computer vision models, or queries per second for inference services. High throughput ensures scalability and cost-efficiency, allowing systems to handle concurrent user demands without significant latency. Optimizing throughput involves techniques like batching, model quantization, and efficient hardware utilization.
Summary
Throughput measures the amount of data or requests an AI system can process successfully within a given timeframe.
Key Concepts
- Performance Metric
- Scalability
- Batching
- Latency vs. Throughput
Use Cases
- LLM Inference Serving
- Real-time Video Processing
- High-concurrency API Design