{"title":"C - to - D-Wave:量子退火器的高级C编译框架","authors":"Mohamed W. Hassan, S. Pakin, Wu-chun Feng","doi":"10.1109/HPEC.2019.8916231","DOIUrl":null,"url":null,"abstract":"A quantum annealer solves optimization problems by exploiting quantum effects. Problems are represented as Hamiltonian functions that define an energy landscape. The quantum-annealing hardware relaxes to a solution corresponding to the ground state of the energy landscape. Expressing arbitrary programming problems in terms of real-valued Hamiltonian-function coefficients is unintuitive and challenging. This paper addresses the difficulty of programming quantum annealers by presenting a compilation framework that compiles a subset of C code to a quantum machine instruction (QMI) to be executed on a quantum annealer. Our work is based on a modular software stack that facilitates programming D-Wave quantum annealers by successively lowering code from C to Verilog to a symbolic “quantum macro assembly language” and finally to a device-specific Hamiltonian function. We demonstrate the capabilities of our software stack on a set of problems written in C and executed on a D-Wave 2000Q quantum annealer.","PeriodicalId":184253,"journal":{"name":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"C to D-Wave: A High-level C Compilation Framework for Quantum Annealers\",\"authors\":\"Mohamed W. Hassan, S. Pakin, Wu-chun Feng\",\"doi\":\"10.1109/HPEC.2019.8916231\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A quantum annealer solves optimization problems by exploiting quantum effects. Problems are represented as Hamiltonian functions that define an energy landscape. The quantum-annealing hardware relaxes to a solution corresponding to the ground state of the energy landscape. Expressing arbitrary programming problems in terms of real-valued Hamiltonian-function coefficients is unintuitive and challenging. This paper addresses the difficulty of programming quantum annealers by presenting a compilation framework that compiles a subset of C code to a quantum machine instruction (QMI) to be executed on a quantum annealer. Our work is based on a modular software stack that facilitates programming D-Wave quantum annealers by successively lowering code from C to Verilog to a symbolic “quantum macro assembly language” and finally to a device-specific Hamiltonian function. We demonstrate the capabilities of our software stack on a set of problems written in C and executed on a D-Wave 2000Q quantum annealer.\",\"PeriodicalId\":184253,\"journal\":{\"name\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"volume\":\"277 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE High Performance Extreme Computing Conference (HPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC.2019.8916231\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE High Performance Extreme Computing Conference (HPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2019.8916231","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
C to D-Wave: A High-level C Compilation Framework for Quantum Annealers
A quantum annealer solves optimization problems by exploiting quantum effects. Problems are represented as Hamiltonian functions that define an energy landscape. The quantum-annealing hardware relaxes to a solution corresponding to the ground state of the energy landscape. Expressing arbitrary programming problems in terms of real-valued Hamiltonian-function coefficients is unintuitive and challenging. This paper addresses the difficulty of programming quantum annealers by presenting a compilation framework that compiles a subset of C code to a quantum machine instruction (QMI) to be executed on a quantum annealer. Our work is based on a modular software stack that facilitates programming D-Wave quantum annealers by successively lowering code from C to Verilog to a symbolic “quantum macro assembly language” and finally to a device-specific Hamiltonian function. We demonstrate the capabilities of our software stack on a set of problems written in C and executed on a D-Wave 2000Q quantum annealer.