• Yaroslav Kharkov

Arline Benchmarks (Part 1): Benchmarking in Quantum World

Have you ever thought of buying a gaming laptop/PC and browsed through numerous youtube review videos of various hardware specs? And compare their pros and cons by skimming through dozens of benchmarking charts, plots, numbers and desperately attempting to make a final decision which product to pick?


Most likely yes!



And there is a good reason why it is worthwhile doing that: when you buy a gaming laptop you want the hardware performance to satisfy our needs. And surely your needs depend on what type of games you are playing, what OS you are planning to install and it vastly varies from user to user.


Interestingly, a rather similar problem also exists in a completely different world, the world of quantum computing. With a fast pace of innovation in the realm of quantum hardware, it is becoming more and more important to understand strengths and weaknesses of quantum processors as well as their suitability for various types of quantum algorithms.



Clearly, quantum computing is still an emerging technology today, it may have a long path ahead before creating real value and being commercially viable. Mostly scientists, quantum enthusiasts and researchers who are adopting quantum computing and driving the innovation forward.


Benchmarking of quantum hardware, quantum algorithms and quantum compilers are of high importance nowadays, because in order to better understand the strengths and limitations of quantum computation we need to squeeze out maximum performance from small scale devices available today.


Like in the early days of classical computers Lakeside Programmers Club, formed by Bill Gates, Paul Allen and their friends, was squeezing out maximum performance out of PDP-10 and understanding the potential on a new machine, quantum computation does require somewhat similar actions to discover the strengths and limitations of state-of-the-art devices.


With different types of quantum hardware available today, benchmarking of quantum architectures, quantum algorithms and quantum compilers become an important topic nowadays. And yes, as it turns out an efficient compilation of algorithms for particular quantum hardware is one of the keys to unlock the full power of a particular device.


Here we present a new open-source platform, Arline Benchmarks that is designed for performing a fair benchmarking of quantum hardware, quantum compilation frameworks on the same set of quantum algorithms. The main focus of Arline Benchmarks is to provide an insight into a rather complicated process of quantum compilation that could be used to optimise existing compilation subroutines.


As a result of benchmarking analysis, Arline Benchmarks automatically generates a user-friendly PDF report with analytics, charts and detailed information about each stage of the compilation pipeline.


With this post, we are launching the series of posts which concern quantum computing, quantum compilers and benchmarking of quantum algos, frameworks and quantum hardware.


Let’s start our quantum journey!


To be continued. We will come back with the next episode soon!


More Episodes:

Part 2. Arline Benchmarks: Quantum Computing in a Nutshell


Our Github:

github.com/ArlineQ