When running SPECrate 2017 Floating Point and Integer benchmarks on two Azure VMs, the performance results varied more for Floating Point workloads. SPECrate 2017 Floating Point tests 13 floating point workloads used in fields like engineering, modeling, and finance. These types of workloads may provide a better indicator of performance for applications heavily using floating point calculations compared to integer-focused SPECrate 2017 results. Organizations should consider running workload benchmarks more specific to their needs to help choose the best optimized cloud VM.

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When we ran SPECrate 2017 Floating Point workloads on two Microsoft Azure VMs,
the performance differences varied considerably from SPECrate 2017 Integer scores
Get a clearer picture of potential cloud
performance by looking beyond SPECrate 2017 Integer scores
with SPECrate 2017 Floating Point
Learn more about the other real-world workloads we ran at https://facts.pt/odi9nGQ
What’s the best way to gauge cloud instance performance? Using an industry-standard benchmark from the
SPEC CPU 2017 benchmark package, such as SPECrate 2017 Integer, can deliver good compute performance
data. But it may not paint the same picture as workloads more directly representative of your applications.
Running SPECrate 2017 Integer—which uses a broad range of applications that target the processor, memory,
and compilers—we saw the following results on the Azure VMs we tested:
As another part of the SPEC CPU 2017 package, the SPECrate 2017 Floating Point suite includes
13 floating point workloads, such as explosion modeling, fluid dynamics, molecular dynamics,
weather forecasting, computational electromagnetics, and regional ocean modeling. We saw
the following results, which the benchmark reports as an aggregate of the workloads:
Why test with SPECrate
2017 Floating Point?
Engineering workloads, technical calculations, and financial transactions all rely on floating point calculations
as opposed to integer calculations. By testing this more specific type of performance, organizations that run
these workloads could have better luck choosing a cloud VM that optimizes the performance they need.
Get the bigger picture when you branch out to specific workloads.
SPECrate 2017 Floating Point performance Higher is better
fp_base
rate
D16ds_v5 with Intel Xeon Scalable processors D16ads_v5 with AMD EPYC processors
100
63.3
0 20 40 60 80 100 120
SPECrate 2017 Integer performance Higher is better
0 10 20 30 40 50 60 70 80
D16ds_v5 with Intel®
Xeon®
Scalable processors D16ads_v5 with AMD EPYC™
processors
int_base
rate
71.9
66
SPECrate 2017
Floating Point
Compute-intensive