AMD EPYC 3251 Benchmarks
For this exercise, we are using our legacy Linux-Bench scripts which help us see cross-platform “least common denominator” results we have been using for years as well as several results from our updated Linux-Bench2 scripts. At this point, our benchmarking sessions take days to run and we are generating well over a thousand data points. We are also running workloads for software companies that want to see how their software works on the latest hardware. As a result, this is a small sample of the data we are collecting and can share publicly. Our position is always that we are happy to provide some free data but we also have services to let companies run their own workloads in our lab, such as with our DemoEval service. What we do provide is an extremely controlled environment where we know every step is exactly the same and each run is done in a real-world data center, not a test bench.
Python Linux 4.4.2 Kernel Compile Benchmark
This is one of the most requested benchmarks for STH over the past few years. The task was simple, we have a standard configuration file, the Linux 4.4.2 kernel from kernel.org, and make the standard auto-generated configuration utilizing every thread in the system. We are expressing results in terms of compiles per hour to make the results easier to read.
Performance is right alongside what we are we would expect from an 8-core AMD EPYC Zen core CPU. You can see that it is in the middle of 8-core Intel Xeon Skylake offerings.
c-ray 1.1 Performance
We have been using c-ray for our performance testing for years now. It is a ray tracing benchmark that is extremely popular to show differences in processors under multi-threaded workloads. Our previous generation benchmark suite uses a 4K resolution test. We normally do not publish this anymore since higher-end SKUs do not offer enough differentiation. Since our data set is larger with the 4K tests on the embedded side, we wanted to get some numbers out there.
We are using our new Linux-Bench2 8K render to show differences.
Since this is a less memory-bandwidth constrained workload, we see a really interesting pattern. The AMD EPYC 3251 out-performs the 8-core AMD EPYC 7251 by the narrowest of margins.
7-zip Compression Performance
7-zip is a widely used compression/ decompression program that works cross-platform. We started using the program during our early days with Windows testing. It is now part of Linux-Bench.
A quick note here, this result is sorted on the decompression speed. That is important because both the AMD EPYC 3251, other AMD EPYC architectures, and Intel Atom C3955 all have higher decompression versus compression speeds. Skylake architectures are flipped with higher compression numbers, so sorting matters.
Performance of the AMD EPYC 3251 is generally great and is competitive with a 12-core Intel Xeon D-1557 or an 8 core Intel Xeon D-2141I.
NAMD is a molecular modeling benchmark developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. More information on the benchmark can be found here. We are going to augment this with GROMACS in the next-generation Linux-Bench in the near future. With GROMACS we have been working hard to support Intel’s Skylake AVX-512 and AVX2 supporting AMD Zen architecture. Here are the comparison results for the legacy data set:
Here we see performance matching the Intel Xeon D-2141I and significantly outpacing the D-1541. That is a trend, however, we will see a different story on the more optimized tests that can use AVX2/ AVX-512.
Sysbench CPU test
Sysbench is another one of those widely used Linux benchmarks. We specifically are using the CPU test, not the OLTP test that we use for some storage testing.
Here again, we see solid performance closer to a 12-core Intel Xeon D-1557 CPU and between the Intel Xeon Silver 4108 and 4110 8-core offerings. The Skylake-D 8-core Intel Xeon D-2141I is incrementally faster, but the AMD EPYC 3251 puts forth a strong showing.