Overview Resources

Altair® FlowTracer™

Mission-critical Dependency Management and Flow Visualization

The all-new Altair® FlowTracer™ — modernized and enhanced for today’s engineering challenges — is an advanced design flow visualization, development, and execution platform. FlowTracer visualizes and analyzes complex flows and identifies their inherent parallelism to optimize compute resources on-premises and in the cloud. It empowers users to create, manage, and execute design flows across a variety of applications – including semiconductor design, algorithm evaluation, and software development – and to handle the latest artificial intelligence (AI) and machine learning workflows.

FlowTracer captures and updates flows by interacting with tools while they’re executing commands contained in the flows, a unique tracing technique for managing dependencies between files and tools. Users can work natively in any modern programming language, view and control complex workflows via multiple devices, and get high-performance flow definition with secure connectivity.

FlowTracer Overview Video

Why FlowTracer?

Benefits for Designers

Greater productivity through flow visualization and control, plus dependency management and awareness for faster turnaround time.

Benefits for the Infrastructure

Improved resource utilization through parallel execution, a small memory footprint, and built-in scheduler for greater scalability

Benefits for Management

Reduced design flow complexity for higher-quality results, plus flow standardization and better collaboration

Key Benefits

Real-Time Reporting

FlowTracer’s powerful Grid View report displays the results of millions of running jobs and highlights failing jobs so they can be quickly identified, debugged, and resolved.

AI and Machine Learning Workflows

FlowTracer integrates with AI and machine learning workflows using popular development languages including Python, Julia, and Jupyter Notebook.

Hybrid Design Workflows

Users can bring AI and machine learning services into traditional workflows and run a mix of both types of jobs, working alongside or on top of Kubernetes clusters. Flows dynamically adapt to resource availability and the results of previous calculations.

REST-Based Access

The full REST application programming interface (API) enables users to define and control flows in their preferred language.

JSON-Based Flow Description

Building on the REST API, the JSON-based Flow Definition Notation (FDN) allows efficient transfer of workflow definitions from clients into the FlowTracer engine. A single POST can transfer complete design flows – with tens of thousands of jobs and dependencies – in just a few seconds.

Your Choice of Platform

Users can view and control complex workflows in various operating modes, including interactive, supervised, and lights-out batch mode — and on Windows or Linux x86/ARM platforms using a command line, REST interface, or web browser.

Dependency Management and Awareness

Dependency awareness prevents jobs from being executed until all prior dependency requirements are met, enabling users to quickly identify the root cause of failing jobs, take corrective action, and continue running the jobs from the point of failure without having to restart.

Fast, Scalable Development

FlowTracer has a small memory footprint and built-in scheduler. It enables users to run complex flows locally on a laptop or dedicated host with GPUs, connect to a batch system, or go to the cloud — a scalable solution that can handle millions of jobs in memory and thousands running simultaneously.

Connected Collaboration

With FlowTracer's remote connectivity, users can collaborate with domain experts by sharing mirrored views in real time. Complex design workflows are easily deployed and shared across organizations for easy and effective flow management, standardization, and collaboration.