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ChemIT currently does not have plans nor resources to invest in R&D or consulting services to help CCB researchers evaluate or utilize the power of cloud computing for research. However, this page can raise awareness of these new services' potential to advance CCB computing, cost-effectively. |
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See also
- Restricted: Two CU researcherresearchers' s Cloud case-studystudies (Cornell NetID required; cited below, too)
- Ramping up and down cloud services to save money
- Cornell's own CAC’s RedCloud:
- http://cloudcomputing.cornell.edu/Research.php (added 3/20/15)
- This is sponsored by the Computer Science department. (Not tied to CIT or CAC.)
- http://itnews.cornell.edu/cloudification-services-will-offer-ramp-cloud-infrastructure (3/13/15 CIT article)
- A Cornell IT manager peer shared this nice digestible interview/talk with one of his favorite experts talking about cloud and IT for life sciences:
Chemistry "case study" of a web server, hosted using Amazon's Web Service (AWS)
- September 2016: CIT successfully packaged old NMR Scheduler's Python code and text files and moved it to contemporary OS and web server software running on AWS. They had been running on an old, not patched or maintained, Linux and Apache public web server.
- Automatic monthly billing via internal Cornell KFS. Over the past week (9/9/16), the NMR Scheduler AWS resources cost about $0.20/day Expect to see this rise a little when we release it. Still CIT folks would be very surprised if it was more than $0.50/day all told.
- For 365 days/ year, that comes out to ~$73-183/year for a patched and otherwise maintained Linux and Apache public web server running custom, old Perl scripts. And one easily replicated, if necessary.
- AWS Standard Tagging
Cornell "case study", using Amazon's Web Service (AWS)
The "case study" cited here contains examples of innovative use of cloud-based infrastructure for provisioning research-based computing power similar to what CCB researchers get by investing in high-performance computers and clusters.
N.B. Other academic departments in A&S which could benefit from cloud computing, per Frank Strickland (3/20/15), include Linguistics, Anthropology, Psychology, and Econ. Some of these are listed in the DNSDB entry for Cornell's cloud computing research hub.
- Restricted: Two CU researcherresearchers' s Cloud case-studystudies (Cornell NetID required)
In addition to Amazon, services and providers in this space include Cornell's own CAC’s RedCloud, as well as Google Compute Engine and Microsoft Azure.
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| Offering | Core count compared (performance, though?) | RAM (FWIW) | Cost | Cost comparison |
|---|---|---|---|---|
| ChemIT | 48 cores (6 cores/ proc. * | 32-64GB, usually | $10,000 total hardware (~$2,600/computer * | $2,500/ yr (Assumes last 4 years, 3 of which are under warranty) Lots of local IT labor costs. (Maybe $10K/ yr, at least for first set of 4?) |
| Google Compute | 32 cores (8 cores/ computer * | 30GB | $1,132.10 per month. (Used Google Compute's calculator, | $13,585.20/ yr No local IT labor costs. |
Google Compute: More cores and RAM | 64 cores (16 cores/ computer * | 60GB | $2,264.19 per month. (Used Google Compute's calculator, | $27,170.28/ yr No local IT labor costs. |
Google Compute: More cores, less RAM | 64 cores (16 cores/ computer * | 14.4GB | $1,423.21 per month. (Used Google Compute's calculator, | $17,078.52/ yr No local IT labor costs. |
Articles
http://www.theregister.co.uk/2016/02/15/nice_catch_amazon_bezos_buys_hpc_toolkit_from_italy/
- AWS already offers HPC-clusters-as-a-service. Once it beds in NICE, it will also have a fine way to make those clusters attack certain workloads. And once it is in that position, it will be in a position to take more of the HPC market and give yet another corner of on-premises kit market a kicking.
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February 26, 2014: Ultimate cloud speed tests: Amazon vs. Google vs. Windows Azure
A diverse set of real-world Java benchmarks shows Google is fastest, Azure is slowest, and Amazon is priciest.
Vendor links
Links to vendors not linked in any of the above analysis sections.
http://research.microsoft.com/en-us/projects/azure/
The Microsoft Azure for Research project facilitates and accelerates scholarly and scientific research by enabling researchers to use the power of Microsoft Azure to perform big data computations in the cloud. Take full advantage of the power and scalability of cloud computing for collaboration, computation, and data-intensive processing. Microsoft Azure is an open platform that supports languages, tools, or frameworks, such as Linux [...].
http://research.microsoft.com/en-us/projects/azure/technical-papers.aspx
The information in these papers can be used by Windows, Linux, and Mac users. If you have attended the Microsoft Azure for Research training, have received an award through the RFP program, or are just curious about Microsoft Azure, we believe you will find this content useful. The papers do assume some prior technical computer programming skills, such as Python, Matlab, and basic scripting.
Other
Roger's thoughts, from 7/30/14:
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