RosneT: A Block Tensor Algebra Library for Out-of-Core Quantum Computing Simulation

TL;DR

RosneT is a distributed, out-of-core tensor algebra library designed for scalable quantum circuit simulation on supercomputers, enabling simulations of up to 53 qubits.

Contribution

It introduces RosneT, a novel library leveraging task-based parallelism for tensor contractions in quantum simulations on exascale systems.

Findings

Good scalability demonstrated up to 53 qubits

Effective out-of-core tensor operations on supercomputers

Utilization of PyCOMPSs for task management

Abstract

With the advent of more powerful Quantum Computers, the need for larger Quantum Simulations has boosted. As the amount of resources grows exponentially with size of the target system Tensor Networks emerge as an optimal framework with which we represent Quantum States in tensor factorizations. As the extent of a tensor network increases, so does the size of intermediate tensors requiring HPC tools for their manipulation. Simulations of medium-sized circuits cannot fit on local memory, and solutions for distributed contraction of tensors are scarce. In this work we present RosneT, a library for distributed, out-of-core block tensor algebra. We use the PyCOMPSs programming model to transform tensor operations into a collection of tasks handled by the COMPSs runtime, targeting executions in existing and upcoming Exascale supercomputers. We report results validating our approach showing good scalability in simulations of Quantum circuits of up to 53 qubits.