Tour of TT-Lang

TT-Lang is a Python-based domain-specific language for authoring high-performance custom operations on Tenstorrent hardware.

Overview

TT-Lang provides an expressive middle ground between TT-NN’s high-level operations and TT-Metalium’s low-level hardware control. The language centers on explicit data movement and compute kernels with synchronization primitives familiar to TT-Metalium users (dataflow buffers, semaphores) alongside new abstractions (tensor slices, blocks, pipes).

Key Concepts

• Operation function: Python function decorated with @ttl.operation() that defines kernel functions.

• Kernel functions: Decorated with @ttl.compute() or @ttl.datamovement(), these define compute and data movement logic.

• Dataflow buffers: Communication primitives for passing data between kernels within a node.

• Blocks: Memory acquired from dataflow buffers, used in compute expressions or copy operations.

• Grid: Defines the space of nodes for operation execution.

Tour

• Operation Basics
  • Operation Function
  • Kernel Functions
  • Grid and Node Functions
• Dataflow Buffers
  • Overview
  • Acquisition Functions
  • Example
  • API Reference

Reference

For the complete language specification, see TT-Lang Specification.