TAMM: Tensor Algebra for Many-body Methods

Abstract

Tensor contraction operations in computational chemistry consume significant fractions of computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. The TAMM framework decouples the specification of the computation and the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM whereas high-performance computing developers can focus on various optimizations on the underlying constructs such as efficient data distribution, optimized scheduling algorithms, efficient use of intra-node resources (e.g., GPUs). The modular structure of TAMM allows it to be extended to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to sustainable development of tensor contraction-based methods in computational chemistry applications. We present case studies that highlight the ease of use as well as the performance and productivity gains compared to other implementations.

References in corpus (8)

• NWChem: Past, Present, and Future
• Time-dependent coupled-cluster method for atomic nuclei
• Equation of motion coupled-cluster approach for intrinsic losses in x-ray spectra
• Numerical stability of time-dependent coupled-cluster methods for many-electron dynamics in intense laser pulses
• Time-dependent optimized coupled-cluster method for multielectron dynamics II. A coupled electron-pair approximation
• DISTAL: The Distributed Tensor Algebra Compiler
• GFCCLib: Scalable and Efficient Coupled-Cluster Green's Function Library for Accurately Tackling Many Body Electronic Structure Problems
• SpDISTAL: Compiling Distributed Sparse Tensor Computations

Cited by in corpus (6)

• Roadmap on Electronic Structure Codes in the Exascale Era
• "Best" iterative coupled-cluster triples model: More evidence for 3CC
• Generating coupled cluster code for modern distributed memory tensor software
• Elucidating Many-Body Effects in Molecular Core Spectra through Real-Time Approaches: Efficient Classical Approximations and a Quantum Perspective
• Implementation of Tensor Network Simulation TN-Sim under NWQ-Sim
• Ricci-Notation Tensor Framework for Model-based Approaches to Imaging