Quantum computers are the biggest jump forward in processing power that the industry has seen in decades. As part of this revolution it is necessary to change our approach to algorithm design. D-Wave is one of the companies who are pushing the boundaries in quantum processing and they have created a Python SDK for experimenting with quantum algorithms. In this episode Alexander Condello explains what is involved in designing and implementing these algorithms, how the Ocean SDK helps you in that endeavor, and what types of problems are well suited to this approach.
Do you want to try out some of the tools and applications that you heard about on Podcast.__init__? Do you have a side project that you want to share with the world? With Linode’s managed Kubernetes platform it’s now even easier to get started with the latest in cloud technologies. With the combined power of the leading container orchestrator and the speed and reliability of Linode’s object storage, node balancers, block storage, and dedicated CPU or GPU instances, you’ve got everything you need to scale up. Go to pythonpodcast.com/linode today and get a $60 credit to launch a new cluster, run a server, upload some data, or… And don’t forget to thank them for being a long time supporter of Podcast.__init__!
- Hello and welcome to Podcast.__init__, the podcast about Python and the people who make it great.
- When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With 200 Gbit/s private networking, scalable shared block storage, node balancers, and a 40 Gbit/s public network, all controlled by a brand new API you’ve got everything you need to scale up. And for your tasks that need fast computation, such as training machine learning models, they just launched dedicated CPU instances. Go to pythonpodcast.com/linode to get a $20 credit and launch a new server in under a minute. And don’t forget to thank them for their continued support of this show!
- You listen to this show to learn and stay up to date with the ways that Python is being used, including the latest in machine learning and data analysis. For even more opportunities to meet, listen, and learn from your peers you don’t want to miss out on this year’s conference season. We have partnered with organizations such as O’Reilly Media, Dataversity, Corinium Global Intelligence, Alluxio, and Data Council. Upcoming events include the combined events of the Data Architecture Summit and Graphorum, the Data Orchestration Summit, and Data Council in NYC. Go to pythonpodcast.com/conferences to learn more about these and other events, and take advantage of our partner discounts to save money when you register today.
- Your host as usual is Tobias Macey and today I’m interviewing Alex Condello about the Ocean SDK from D-Wave for building quantum algorithms in Python
- How did you get introduced to Python?
- Can you start by giving a high-level overview of quantum computing?
- What is the Ocean SDK and how does it fit into the business model for D-Wave?
- What are some of the problem types that a quantum processor is uniquely well suited for?
- How does the overall system design for a quantum computer compare to that of the Von Neumann architecture that is common for the machines that we are all familiar with?
- What are some of the differences in algorithm design when programming for a quantum processor?
- Is there any specialized background knowledge that is necessary for making effective use of the QPU’s capabilities?
- What are some of the common difficulties that you have seen users struggle with?
- How does the Ocean SDK assist the developer in implementing and understanding the patterns necessary for Quantum algorithms?
- What was the motivation for choosing Python as the target language for an SDK to attract developers to experiment with quantum algorithms?
- Can you describe how the SDK is implemented and some of the integrations that are necessary for being able to operate on a quantum processor?
- What have you found to be some of the most interesting, challenging, or unexpected aspects of your work on the Ocean software stack?
- How do you handle the abstraction of the execution context to allow for replicating the program behavior on CPU/GPU vs QPU
- Is there any potential for quantum computing to impact research in previously intractable computer science research, such as the P vs NP problem?
- What are your current scaling limits in terms of providing compute to customers for their problems?
- What are some of the most interesting, innovative, or unexpected ways that you have seen developers use the Ocean SDK and quantum processors?
- What are you most excited for as you look to the future capabilities of quantum systems?
- What are some of the upcoming challenges that you anticipate for the quantum computing industry?
Keep In Touch
- arcondello on GitHub
- Ocean SDK
- Quantum Computing
- Quantum Annealing
- Quantum Superposition
- D-Wave Leap
- Von Neumann Architecture
- Linear Programming
- D-Wave ML Papers
- D-Wave NetworkX
- Maximum Cut Problem
- Ising Problem
- Los Alamos National Laboratory
- Vertex Cover Problem
- D-Wave Hybrid