Cyclops Tensor Framework: Reducing Communication and Eliminating Load Imbalance in Massively Parallel Contractions

Abstract

Cyclops (cyclic-operations) Tensor Framework (CTF) 1 is a distributed library for tensor contractions. CTF aims to scale high-dimensional tensor contractions such as those required in the Coupled Cluster (CC) electronic structure method to massively-parallel supercomputers. The framework preserves tensor structure by subdividing tensors cyclically, producing a regular parallel decomposition. An internal virtualization layer provides completely general mapping support while maintaining ideal load balance. The mapping framework decides on the best mapping for each tensor contraction at run-time via explicit calculations of memory usage and communication volume. CTF employs a general redistribution kernel, which transposes tensors of any dimension between arbitrary distributed layouts, yet touches each piece of data only once. Sequential symmetric contractions are reduced to matrix multiplication calls via tensor index transpositions and partial unpacking. The user-level interface elegantly expresses arbitrary-dimensional generalized tensor contractions in the form of a domain specific language. We demonstrate performance of CC with single and double excitations on 8192 nodes of Blue Gene/Q and show that CTF outperforms NWChem on Cray XE6 supercomputers for benchmarked systems.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Feb 13, 2013
Accession Number
ADA580199

Entities

People

  • Devin A Matthews
  • Edgar Solomonik
  • James Demmel
  • Jeff R. Hammond

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Band Structures
  • Chemistry
  • Computational Chemistry Methods
  • Computational Science
  • Computations
  • Computer Science
  • Computers
  • Computing System Architectures
  • Decomposition
  • Floating Point Operations
  • Language
  • Network Architecture
  • Quantum Chemistry
  • Three Dimensional
  • Virtualization
  • Wave Functions

Readers

  • Computational Fluid Dynamics (CFD)
  • Graph Algorithms and Convex Optimization.
  • Linear Algebra

Technology Areas

  • Microelectronics