What is TT-NN Visualizer?

The visualiser is a diagnostic tool for visualizing the Tenstorrent Neural Network model (TT-NN).

The app is available to install via PyPI or hosted online. You may also build and run from source.

Features

Reports

Upload reports from the local file system or sync remotely via SSH
Switch seamlessly between previously uploaded or synced reports
Run multiple instances of the application concurrently with different data
Set data ranges for both memory and performance traces
Display physical topology and configuration of Tenstorrent chip clusters

Operations

Filterable list of all operations in the model
Interactive memory and tensor visualizations, including per core allocations, memory layout, allocation over time
Input/output tensors details per operation including allocation details per core
Navigable device operation tree with associated buffers and circular buffers

Tensors

List of tensor details filterable by buffer type
Flagging of high consumer or late deallocated tensors

Buffers

Visual overview of all buffers for the entire model run by L1 or DRAM memory
Toggle additional overlays such as memory layouts or late deallocated tensors
Ease of navigation to the relevant operation
Track a specific buffer in the data across the application
Filterable table view for a more schematic look at buffers

Graph

Interactive model graph view showing all operations and connecting tensors
Filter out deallocated operations
Find all operations by name

Performance

Integration with tt-perf-report and rendering of performance analysis
Interactive charts and tables
Multiple filtering options of performance data
Compare multiple performance traces

NPE

Network-on-chip performance estimator (NPE) for Tenstorrent Tensix-based devices
Dedicated NPE visualizations: zones, transfers, congestion, timelines with elaborate filtering capability

For the latest updates see releases.