Then it produces the second metric called critical jOps, where it's monitoring all of the workload against a latency SLA. This really is great at measuring the maximum amount of work we can get done on a server. One of the reasons we really find SPECjbb useful is it produces two different metrics that characterize the system differently.
We used OpenJDK 17 because it's the most recent long term supported release.
We chose SPECjbb because we use it internally often to model against our other workloads that run in the JDK that are predominantly written in either Scala or Java. In this case, we use SPECjbb 2015, and OpenJDK 17 to gauge the performance of both throughput and latency response. We're going to discuss some notable differences in performance. We're going to talk about the three different publicly available architectures from AMD, Intel, and Arm. We wouldn't have time and a lot of machine learning workloads are a subspecialty among themselves. One of the things I want to point out, though, about performance in terms of this presentation, is we're not going to address machine learning workloads. You're going to be paying for the electricity to run them, it can become important.
Whenever you purchase these servers, you're going to be able to get a certain number of them into certain power footprints. Lastly, when you're talking about building your own fleet, what's the performance per watt? This is going to become a lot more important when your server numbers grow. Then you have to think about, are there going to be issues from the fact that you're now dealing with non-uniform memory. Then you can go another level on top of this and talk about a system level where you can arrange multiple packages from each server vendor and make even bigger servers. Then another dimension of this is, what is the CPU or the socket architecture? That means, in each package from each one of these vendors, do you get enough cores, do you get enough memory bandwidth, do you get enough I/O bandwidth for your workload. Really, this is about whether or not each core or thread you're running meets performance expectations. One of the things that this can refer to is the core performance or the core architecture. Singer: Let's kick things off by talking about how performance and architecture can refer to different things. Performance and Architecture Can Refer to Different Things I'm a senior hardware engineer at Twitter. I'm a senior staff hardware engineer at Twitter.īalk: I'm Jeff Balk.
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