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International Computer Engineering Conference

Towards an intelligent and complete compiler for conventional computer with Co-Quantum processor

H. A. Ali, Ahmed I. Saleh, El-Mahdy M. Ameen

Published Dec 1, 2012• 3 citations
Publisher

Abstract

This paper presents a proposed architecture for constructing a universal complete compiler for conventional-quantum computing machines. Our proposed compiler will receive a well known high level programming language as a source program, after that it will classify the operation of the whole central processing unit into two categories; the first for Co-Quantum processor to execute the complicated quantum computations. The second, for the classical processor which plays the role of performing conventional tasks such as network communication process, storing data tasks and the main task of controlling all system operations. We present a design flow that transforms a high-level language program representing a computing algorithm into a technology-specific implementation. We show the significant steps in this flow and illustrate the transformations to the representation of the classical and quantum program instructions.

DOI
10.1109/icenco.2012.6487098

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This paper presents a proposed architecture for constructing a universal complete compiler for conventional-quantum computing machines. Our proposed compiler will receive a well known high level programming language as a source program, after that it will classify the operation of the whole central processing unit into two categories; the first for Co-Quantum processor to execute the complicated quantum computations. The second, for the classical processor which plays the role of performing conventional tasks such as network communication process, storing data tasks and the main task of controlling all system operations. We present a design flow that transforms a high-level language program representing a computing algorithm into a technology-specific implementation. We show the significant steps in this flow and illustrate the transformations to the representation of the classical and quantum program instructions.
Compilers and computer-aided design tools will be essential for quantum computing. We present a computer-aided design flow that transforms a highlevel language program representing a quantum computing algorithm into a technology-specific implementation. We trace the significant steps in this flow and illustrate the transformations to the representation of the quantum program. The focus of this paper is on the languages and transformations needed to represent and optimize a quantum algorithm along the design flow.
Abstract Quantum computers promise to transform our notions of computation by offering a completely new paradigm. To achieve scalable quantum computation, optimizing compilers and a corresponding software design flow will be essential. We present a software architecture for compiling quantum programs from a high-level language program to hardware-specific instructions. We describe the necessary layers of abstraction and their differences and similarities to classical layers of a computer-aided design flow. For each layer of the stack, we discuss the underlying methods for compilation and optimization. Our software methodology facilitates more rapid innovation among quantum algorithm designers, quantum hardware engineers, and experimentalists. It enables scalable compilation of complex quantum algorithms and can be targeted to any specific quantum hardware implementation.
Building a quantum computer is not only about having qubits or quantum processors, analogously to classical computers are not only based on transistors or integrated circuits. Accordingly, in the very recent times, a few unique research groups in academia and companies have been exploring and proposing high-level and low-level programming languages, compilers, microarchitecture and instruction set architectures for quantum computation as well as different computer architecture approaches. In other words, developing a quantum computer requires bridging quantum applications and quantum devices. This talk will address the main challenges of building a scalable full-stack quantum computing system followed by a discussion on its architecture focusing on fault tolerance and compilation of quantum algorithms on NISQ devices. I will also provide my vision on how the research community could accelerate the process towards building such a scalable quantum machine, potentially through vertical cross-layer co-design structured methodologies.
This article presents the definition and implementation of a quantum computer architecture to enable creating a new computational device-a quantum computer as an accelerator. A key question addressed is what such a quantum computer is and how it relates to the classical processor that controls the entire execution process. In this article, we present explicitly the idea of a quantum accelerator that contains the full stack of the layers of an accelerator. Such a stack starts at the highest level describing the target application of the accelerator. The next layer abstracts the quantum logic outlining the algorithm that is to be executed on the quantum accelerator. In our case, the logic is expressed in the universal quantum-classical hybrid computation language developed in the group, called OpenQL, which visualized the quantum processor as a computational accelerator. The OpenQL compiler translates the program to a common assembly language, called cQASM, which can be executed on a quantum simulator. The cQASM represents the instruction set that can be executed by the microarchitecture implemented in the quantum accelerator. In a subsequent step, the compiler can convert the cQASM to generate the eQASM, which is executable on a particular experimental device incorporating the platform-specific parameters. This way, we are able to distinguish clearly the experimental research toward better qubits, and the industrial and societal applications that need to be developed and executed on a quantum device. The first case offers experimental physicists with a full-stack experimental platform using realistic qubits with decoherence and error-rates, whereas the second case offers perfect qubits to the quantum application developer, where there is neither decoherence nor error-rates. We conclude the article by explicitly presenting three examples of full-stack quantum accelerators, for an experimental superconducting processor, for quantum accelerated genome sequencing and for near-term generic optimization problems based on quantum heuristic approaches. The two later full-stack models are currently being actively researched in our group.
Quantum computing is a revolution in computational theory that uses the principles of quantum mechanics to perform computations that are beyond the capacity of classical computers. It works with the special features of the quantum bits or qubits to encode and transform the information in manners conventional bits cannot imagine. A quantum compiler is a software tool designed to translate high-level quantum language code into executable quantum instructions. This paper aims to develop a quantum compiler for translating Quantum Computation Language source codes into quantum bytecodes which can later be executed on a Quantum Virtual Machine. This compiler will have a combinational structure that includes a frontend for interpreting the QCL code, an intermediate representation for optimizing quantum algorithms, and a backend for generating efficient quantum bytecode. Optimization techniques will be applied to improve the functioning of the quantum circuits. The compiler will also include an error handling module to handle the errors. The successful deployment of a quantum compiler for QCL has many implications and unlocks opportunities for advancements in quantum technologies.
As quantum computers continue to improve and support larger, more complex computations, smart control hardware and compilers are needed to efficiently leverage the capabilities of these systems. This paper introduces a novel approach to enhance the execution of quantum algorithms on distributed quantum systems. The proposed method involves the development of a hardware design that supports parallel instruction execution and a compiler that modifies the order of instructions to increase parallelism opportunities. The hardware design can be flexibly configured to facilitate parallel execution of instructions that have identical parameters. Furthermore, the compiler uses the underlying hardware constraints to intelligently reorder and decompose instructions to avoid dependencies. The compiler, hardware, and their combination are evaluated using a runtime calculator and a benchmark quantum algorithm set. The results demonstrate a significant speedup, achieving a maximum average speedup of 16.5x and a maximum single-benchmark speedup of 56.2x relative to a baseline, serial execution model. Furthermore, we show a speedup can be obtained across all benchmarks using any of the proposed hardware schemes, although the degree of speedup is largely dependent on the type of quantum algorithm. Taken together, the results of this paper represent a significant step towards realizing high-performance quantum computing systems.