Tensor Algebra Processing Primitives (TAPP): Towards a Standard for Tensor Operations

2026-01-12

AI Summary

The absence of a unified tensor operation interface leads to tight coupling between applications and hardware, hindering performance portability and dependency management. This work proposes TAPP—a C-based Tensor Algebra Processing Primitives interface—that decouples applications from underlying implementations through formal modeling of tensor contraction operations. TAPP represents the first community-driven standard for general-purpose tensor operations, jointly endorsed by academia and industry. It provides a reference implementation and has been successfully integrated into widely used libraries and quantum chemistry software such as TBLIS, cuTENSOR, and DIRAC, demonstrating its feasibility, cross-platform portability, and effectiveness in simplifying software ecosystems.

Technology Category

• Machine Learning: Matrix & Tensor Methods
• Planning, Routing, and Scheduling: Applications
• Application Domains: Other Applications

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Security and privacy of machine learning and AI applications

Abstract

To address the absence of a universal standard interface for tensor operations, we introduce the Tensor Algebra Processing Primitives (TAPP), a C-based interface designed to decouple the application layer from hardware-specific implementations. We provide a mathematical formulation of tensor contractions and a reference implementation to ensure correctness and facilitate the validation of optimized kernels. Developed through community consensus involving academic and industrial stakeholders, TAPP aims to enable performance portability and resolving dependency challenges. The viability of the standard is demonstrated through successful integrations with the TBLIS and cuTENSOR libraries, as well as the DIRAC quantum chemistry package.

Problem

• tensor operations
• standard interface
• performance portability
• hardware-specific implementations
• dependency management

Innovation

• TAPP
• tensor operations
• performance portability
• standard interface
• tensor contraction