D2 3 Computing e-Infrastructure cost calculations and business _models_vam1-final

e-­‐FISCAL: www.efiscal.eu
EC Contract Number: 283449
utilisation rate of 71.3%. The utilisation rate in the e-­‐FISCAL project has been calculated by taking into account
yearly logical wall clock time and available CPU cores at the end of the period (i.e. 31/12/2011). This assumes that
the number of CPU cores reported at the end of the period is available throughout the year. If this is not the case
(e.g. because of an infrastructure upgrade towards the end of the year), the utilisation rate calculated is
underestimated.
Other interesting findings are the high numbers of depreciation rates for the hardware (average 5 years), the
quite good rates of PUE (of around 1.5 median value) and the percentage of electricity cost (around 15% median
value of all costs).
51% of total costs (median values) is dedicated to personnel costs. It is expected that the personnel costs for a
very large computing centre (in the order of 100,000 cores) can show economy of scale if compared to the same
capacity distributed in smaller sites that are federated together. We discuss this issue in more depth later on.
However, the fact that staffing represents a very significant cost category was expected. Intersect 360 in both its
reports of 2011 and 2012 (Intersect 360, 2011; 2012) mentions that the staffing represents 23% of top–level
budgets. This amount in not directly comparable to e-­‐FISCAL due to the different methodology employed
(Intersect 360 conducts a census on budgets and as such the total acquisition budget of hardware-­‐and not its
depreciation-­‐ is included in the 100% calculation); however, the magnitude is similar. Moreover, they claim that
they expect to see in the near future an increase on the money spent on people to manage and maintain systems,
as the computers and overall IT architectures become more complex.
Finally, our results seem to coincide with earlier findings found in literature as shown in Table 3. However, while
other studies concentrate only on site or centre, e-­‐FISCAL is the first costing study that comes up with conclusions
resulting from an extensive synthesis.
Reference Cost per core
Comments
hour
Hawtin et al. (2012) €0.075 Study for JISC UK -­‐ Differences between
institutions reviewed
US DoE -­‐ Magellan
report (2011)
€0.015 Hopper system – National Energy Research
Scientific Computing Centre-­‐ including storage
sub-­‐ system
Smith (2011) €0.031 Purdue campus, USA
University of
€0.020 Hyak cluster, USA
Washington
Cohen and Karagiannis
(2011)
€ 0.09 –
€ 0.14
Stratified sample of EGI centres -­‐ Assuming
60% utilization ratio – storage cost included,
(costs refer to 2009)
Cohen and Karagiannis
(2011)
€0.08 –
€0.10
Stratified sample of EGI centres -­‐ Assuming
60% utilization ratio – storage cost excluded
(costs refer to 2009)
Table 3 – Literature review summary in relation to Cost per core hour or Cost per core hour
Option 2: Basic Case Split: We also run the e-­‐FISCAL costing model by using as inputs the average and the median
values of all necessary input data from the HPC and the HTC e-­‐FISCAL sub-­‐samples (e.g. the average and the
e-­‐FISCAL : Financial Study for Sustainable Computing e-­‐Infrastructures
Deliverable D2.3 – Computing e-­‐Infrastructures cost estimation and analysis – Pricing and
Business models
45