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Together AI introduces Together Compiler for continuous inference optimization

Together AI released Together Compiler, an agent-based system for continuous compilation in AI inference that adapts to changing workloads.

Together AI introduces Together Compiler for continuous inference optimization — image from Together AI
Image: Together AI

Summary

Together AI has introduced Together Compiler (TKCC), an agent-based continuous compilation system designed to optimize AI inference workloads dynamically. The system uses persistent engines and high-throughput agents to test optimizations without costly engine restarts. According to the company, it achieves higher token-per-second performance across various frontier open-source models and hardware setups.

What changed

  • Introduced Together Compiler (TKCC) for continuous AI inference optimization using high-throughput agents
  • Implemented persistent engines to eliminate engine restart overhead during optimization experiments
  • Built a two-tiered measurement architecture using fast and slow engines to balance throughput and fidelity
  • Created a custom cost model to select parallelism strategies for changing traffic properties

Availability

Available now

“Together Compiler is serving trillions of tokens today.”

Founder takeaway

If you manage large-scale AI inference infrastructure, review the Together Compiler paper to understand how continuous compilation and persistent engines can reduce optimization overhead.

Source

Together AITogether Compiler: Continuous Compilation for AI inference

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