These days if you do almost anything with a computer hooked up to the internet, you’ve probably heard the term “cloud computing”. Well I’m here to tell you that cloud computing actually does mean something and that it is something useful for medical physics! In this post I’m going to take a quick look at the current state of cloud computing research in medial physics and how it got there.
First things, first, what do I mean by cloud computing? Cloud computing generally refers to scalable computing resources, such as data storage, CPU time, or software access, offered over the internet with a pay-as-you-go pricing scheme (and sometimes free). This service can be provided at a few levels: raw server level access (infrastructure as a service, IaaS), pre-configured systems for specific tasks (platform as a service, PaaS), and software as a service, SaaS, e.g. Gmail or Dropbox. The interesting thing about cloud computing is that, suddenly, anyone armed with a network connection, a credit card, and a little know-how can have access to an unprecedented amount of computing resources. This opens up a huge number of computing possibilities for medical physicists, among others.
Starting in the second half of 2009, our research group at the University of New Mexico, the UNM Particle Therapy Group, started investigating using IaaS-style cloud computing as the basis for massively parallel medical physics calculations (read, very fast, large calculations). Our very first results, demonstrating proof-of-concept with proton beam calculations on a “virtual Monte Carlo cluster” of nodes running on Amazon.com’s EC2 service were presented at the XVIth ICCR conference in Amsterdam in May, 2010. We presented a poster of our second set of results at the AAPM annual meeting in July, 2010 and then posted a paper to the arXiv titled “Radiation therapy calculations using an on-demand virtual cluster via cloud computing” http://arxiv.org/abs/1009.5282 (Sept. 2010).
It has been exciting to see the reactions to our posters, talks, and arXiv print, with most physicists immediately seeing the potential benefits offered by the new levels of access to computing resources offered by cloud computing services. Even more exciting is to see the projects subsequently launched by other medical physics researchers.
So what’s happening now?
- Chris Poole, et al (Queensland Univ. of Tech.) posted a note to the arXiv titled “Technical Note: Radiotherapy dose calculations using GEANT4 and the Amazon Elastic Compute Cloud” http://arxiv.org/abs/1105.1408 (May, 2011)
- Chris Poole also posted code used in that project to http://code.google.com/p/manysim/ (May, 2011)
- UNM held a workshop that included tutorials on using cloud computing for medical physics calculations. Sponsored in part by Amazon.com. (May, 2011)
- UNM launched a cloud computing webpage in conjunction with the workshop: http://www.cs.unm.edu/~compmed/PTG/cloud.html (May, 2011)
- At least *seven* cloud computing abstracts at the AAPM/COMP 2011 meeting
- McCloud: Toward 10 Million Monte Carlo Primaries in 5 Minutes for Clinical Use
- Monte-Carlo Simulation in a Cloud Computing Environment with MapReduce
- Toward Real-Time Monte Carlo Simulation Using a Commercial Cloud Computing Infrastructure
- Toward Web-Based Real-Time VMAT and IMRT Inverse Planning Using Cloud Computing
- Fast and Reliable Cone-Beam CT Reconstruction Using Cloud Computing
- Cloud Computing for Interventional Fluoroscopy Dose Assessment
- The Compute Cloud, a Massive Computing Resource for Patient-Independent Monte Carlo Dose Calculations and Other Medical Physics Applications
Compared to our single abstract at AAPM last year, you could claim there has been an “exponential explosion” in interest in cloud computing in medical physics since we presented our first results in 2010! Does this mean we’ll see 50 abstracts in 2012 mentioning cloud computing? (Two points does not a trend make?? ;) )
I look forward to seeing where this new technology will take our field.
*I’m really leaving off all of the (mostly commercial) cloud-based PACS and related radiology software and services. Some of these are mentioned in our paper on the arXiv.