ASRock Rack X470D4U2-2T Benchmarks
We wanted to give some sense of relative performance to more traditional server solutions on the market.
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:
If you read our X470D4U review, you are going to notice these are very similar. Our Ryzen test points were effectively identical between that platform and this X470D4U2-2T. And we are using the same comparison points on the Intel side. We simply wanted to validate that we were getting the same result which is what we would expect with motherboards with the same base.
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.
Here we can see c-ray 8K results that are solid. Performance of AMD Zen, Zen+, and Zen 2 chips tend to be great on this type of benchmark. If you wanted to build out a render farm and still have manageable nodes, then this may make a lot of sense as a solution.
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 tried getting a sample set that crosses a decent spectrum of alternatives to give some anchor points. This included higher-end solutions such as the AMD EPYC 7232P and the Intel Xeon Bronze 3206R which one would find in more mainstream servers. Some of the comparisons are a bit odd. We still wanted to give some grounding as you think about Ryzen compared to other options. AMD EPYC platforms enjoy server vendor support and have more memory and PCIe I/O capacity. If you want major data center software vendor support, you likely want to use EPYC.
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:
Here we can see the AMD Ryzen 1600 AF performs just below the Intel Xeon E-2244G levels while the Ryzen 5 3600 in the platform is a bit faster than the Xeon E-2246G. AMD has significantly lower pricing at a chip level making these important comparisons in the market.
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 now use the results in our mainstream reviews:
Just taking note here that the higher TDPs of these parts can outpace the AMD EPYC 3251 parts. Embedded EPYC platforms can be an alternative, especially at the lower-end where we do not get the major PCIe I/O bumps of the EPYC 3351 and AMD EPYC 3451 dual die parts.
Overall, performance is good if all you are looking to obtain is a lower core count and memory footprint server.
Our test configuration is pretty lightweight and the CPU is rated at 65W, so we were expecting decently low power consumption numbers. These power consumption numbers were gathered with the Ryzen 5 1600 AF CPU, but all three should be similar.
- Idle Power: 26W
- STH 100% Load: 110W
- Maximum observed power: 119W
These results were observed on 120V power using a basic Kill-A-Watt meter. The system is powered by a consumer-grade 80Plus Bronze power supply similar to what is found in many low-power short-depth server chassis.
Next, we are going to discuss some of our closing thoughts around the solution.