[NOTE: these are simply introductory tests and should not be considered scientifically accurate comparisons of the various platforms]

The first run of the tests used the defaults for the parameters as provided in the original sample. The test bed used is detailed here. The net-net is that the calculation is run 100 times and each time contains a loop that runs 1,000,000 times. Each run of the calculation can be run independently of the others as the aggregation/summation is handled in the spreadsheet once the calculations have finished. To provide some protection from anomalies, I ran each test against each platform 10 times with the first run being “cold”.

Results:

The time values on the Y axis are seconds to complete the execution. In this run, a few things jump out:

• The 2-node HPC cluster killed the other two. This is not altogether surprising, especially considering the processor power is significantly better than the other two scenarios and this is the only scenario where the compute is happening on raw hardware (the “local” development machine is virtualized and I believe that the node instances hosted in Azure are also virtualized.
• The HPC cluster took one run to “warm up” after which the performance was remarkably solid.
• The “Local” (sequential) run beat the Azure (parallel) run. At first this might be surprising, but it really isn’t when you think about it. The Azure model has a certain communication overhead for each request (HTTP sending of each request to azure, communication b/t the web and worker roles via the queue, storage of results in the Azure tables, and the retrieval of the results). In this test run, the compute per run is not significant (averaging just over 0.5 seconds on the local box per calculation) and the communication overhead stands out more. It is supposed that in subsequent runs where the compute is heavier, the two will trade places.