ASRock Rack ROMED8-2T Performance
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.
We are going to show off a few results, and highlight a number of interesting data points in this article.
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:
The performance for this platform scales across a wide range of scenarios, even just using the “P” series discounted parts. We have 8 to 64 core options on our list.
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. We are going to use our 8K results which work well at this end of the performance spectrum.
We highlighted this in our recent AMD EPYC 7552 Benchmarks and Review piece, but AMD currently does not have a 48-core “P” series part. With the AMD EPYC 7702P pricing, we think that is likely a better option, but there are 48-core parts we are not showing here as well.
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.
We think the AMD EPYC 7302P, EPYC 7402P, and EPYC 7502P may be the best fits for this platform given their price/ performance. The EPYC 7702P offers the “wow factor” of having a 64-core part but the lower price and core count parts offer a lot of value as well.
OpenSSL is widely used to secure communications between servers. This is an important protocol in many server stacks. We first look at our sign tests:
Here are the verify results:
Something that is important, yet often missed, is that AMD also has “4-channel optimized SKUs” such as the AMD EPYC 7232P and EPYC 7272 we are showing above. These are designed for lower-cost installations where one does not intend to use massive CPU core counts and high memory capacity. We covered this in AMD EPYC 7002 Rome CPUs with Half Memory Bandwidth and in our video:
On a system like the ROMED8-2T, this is an option for those who intend to use the PCIe slots for networking and storage but may not need all of the compute. At the same time, given the speed of PCIe Gen4 devices, it is likely that you will want full memory bandwidth in this platform if heavily relying upon the PCIe Gen4 slots.
Chess is an interesting use case since it has almost unlimited complexity. Over the years, we have received a number of requests to bring back chess benchmarking. We have been profiling systems and are ready to start sharing results:
If you are a systems integrator building bespoke solutions for your clients, then the impact of having an ATX size motherboard with 64-cores and an absolutely massive RAM and PCIe I/O loadout cannot be understated. AMD is able to offer top-bin dual Xeon performance in a single socket and ASRock Rack is putting that performance into a compact ATX form factor.
Next, we are going to end taking a look at the block diagram followed by our final words.