4 ms·

R23 doesn’t have the same SIMD optimizations available for ARM as it does for x86. Anyone using R23 instead of R24, is putting arm at a disadvantage. Notebookc

by dagmx 2y ago

R23 doesn’t have the same SIMD optimizations available for ARM as it does for x86. Anyone using R23 instead of R24, is putting arm at a disadvantage. Notebookcheck is often called out for this and haven’t really addressed why they stick with R23 beyond not wanting to redo tests for older hardware. They are by far the outlier for performance numbers and why the discussion around performance gets muddied.

AnthonyMouse 2y ago
> R23 doesn’t have the same SIMD optimizations available for ARM as it does for x86. The single-thread benchmark is SIMD-heavy? Now it just sounds like Cinebench ST is a useless benchmark because it's putting a parallelizable SIMD workload on a single core. In real life you'd always be running those multi-threaded, whereas the reason people care about ST performance is for the serialized branch-heavy spaghetti code that inherently only runs on one core. "Run the SIMD code, but clamp it to a single thread" is a garbage proxy for that.
- dagmx 2y ago
  Yes, there’s no difference between the single and multi core benchmark other than how many threads get spun up. I’m not sure why you’re trying to equate simd with parallelization. Tbh, a lot of your response seems odd to me because it’s making several incorrect assumptions. You can’t really escape parallelization with how any modern core works, even on a single core. You may have certain operations process concurrently depending on how the cores resources are available at a given time and what is needed. Regardless, SIMD isn’t concurrency. It’s batching. There’s still significant benefit to having SIMD on a single threaded task. There’s a lot of thread overhead to using multiple cores to do something, whereas SIMD lets you effectively batch things on a single core.
  - AnthonyMouse 2y ago
    SIMD workloads generally imply that you're doing the same operation repeatedly. It's literally in the name; single instruction, multiple data. There are occasional cases where that happens but doesn't parallelize well. TLS is probably a good example because you might have to encrypt a network packet and it's big enough to benefit from SIMD but not big enough that the overhead of splitting it across cores is worth it. But most of the time if you're doing the same operation repeatedly you'll benefit from using more cores. Even for TLS, the client might not split the individual connection across multiple cores, but the server is going to handle multiple clients at once in parallel. Heavy workloads like video encoding make this even more apparent. In general the things that benefit from SIMD are parallel tasks that benefit from multiple cores. Compare this with, say, a browser running JavaScript in a single tab. There is nothing to put on another core, you don't know what instructions will be executed next until you get there. This is where people actually care about single-thread performance, and where processors achieve it by using branch prediction etc. But these exercise very different parts of the CPU than SIMD-heavy workloads. The latter can easily fill the execution units of a wide processor that would be stymied by the former.
    - dagmx 2y ago
      This feels like a really absurd stretch of trying to discern SIMD away from stuff like standard integer and float operations. Maybe in the early 90s, but they’re such a part of processor design that you can’t realistically avoid them. Especially for rendering, which is matrix math heavy, you’d have to design something completely bespoke to avoid it. SIMD is a natural necessity for rendering with any kind of performance. And because SIMD is such a part of every mainstream processor, it’s very important that benchmarks show how well they perform. I also don’t understand why you think a JavaScript runtime wouldn’t use SIMD. V8 can make use of SIMD, whether directly targeted or indirectly via the compiler that compiled the runtime itself. If you want to stress very specific parts of a processor, then use something like SPEC. Cinebench is meant to be a realistic reflection of production rendering.
      - AnthonyMouse 2y ago
        > Especially for rendering, which is matrix math heavy, you’d have to design something completely bespoke to avoid it. SIMD is a natural necessity for rendering with any kind of performance. Well sure, but rendering is a classically parallel operation which is regularly implemented as threaded. > I also don’t understand why you think a JavaScript runtime wouldn’t use SIMD. V8 can make use of SIMD, whether directly targeted or indirectly via the compiler that compiled the runtime itself. JavaScript runtimes are executing code, so they'll implement the whole gamut and their execution will depend on what kind of code it actually is. But the common JavaScript code, and the kind presumably being tested in JavaScript benchmarks because it's what people care about, isn't implementing a video encoder using SIMD. It's manipulating DOM objects and parsing short pieces of text input, which is branch-heavy code with lots of indirection and very little use of SIMD if any. > If you want to stress very specific parts of a processor, then use something like SPEC. Cinebench is meant to be a realistic reflection of production rendering. Which is kind of my point. Production rendering is going to be threaded and max out all the cores, which is Cinebench MT. "CineBench ST" is measuring something that nobody does in real life and doesn't even really correlate with the things people actually do. It doesn't represent real threaded workloads (which optimally run on many low-clocked cores, not one high-clocked one) nor real serialized workloads (which are full of conditional jumps and cache misses).

by dagmx 2y ago

AnthonyMouse 2y ago

> R23 doesn’t have the same SIMD optimizations available for ARM as it does for x86. The single-thread benchmark is SIMD-heavy? Now it just sounds like Cinebench ST is a useless benchmark because it's putting a parallelizable SIMD workload on a single core. In real life you'd always be running those multi-threaded, whereas the reason people care about ST performance is for the serialized branch-heavy spaghetti code that inherently only runs on one core. "Run the SIMD code, but clamp it to a single thread" is a garbage proxy for that.

dagmx 2y ago
Yes, there’s no difference between the single and multi core benchmark other than how many threads get spun up. I’m not sure why you’re trying to equate simd with parallelization. Tbh, a lot of your response seems odd to me because it’s making several incorrect assumptions. You can’t really escape parallelization with how any modern core works, even on a single core. You may have certain operations process concurrently depending on how the cores resources are available at a given time and what is needed. Regardless, SIMD isn’t concurrency. It’s batching. There’s still significant benefit to having SIMD on a single threaded task. There’s a lot of thread overhead to using multiple cores to do something, whereas SIMD lets you effectively batch things on a single core.
- AnthonyMouse 2y ago
  SIMD workloads generally imply that you're doing the same operation repeatedly. It's literally in the name; single instruction, multiple data. There are occasional cases where that happens but doesn't parallelize well. TLS is probably a good example because you might have to encrypt a network packet and it's big enough to benefit from SIMD but not big enough that the overhead of splitting it across cores is worth it. But most of the time if you're doing the same operation repeatedly you'll benefit from using more cores. Even for TLS, the client might not split the individual connection across multiple cores, but the server is going to handle multiple clients at once in parallel. Heavy workloads like video encoding make this even more apparent. In general the things that benefit from SIMD are parallel tasks that benefit from multiple cores. Compare this with, say, a browser running JavaScript in a single tab. There is nothing to put on another core, you don't know what instructions will be executed next until you get there. This is where people actually care about single-thread performance, and where processors achieve it by using branch prediction etc. But these exercise very different parts of the CPU than SIMD-heavy workloads. The latter can easily fill the execution units of a wide processor that would be stymied by the former.
  - dagmx 2y ago
    This feels like a really absurd stretch of trying to discern SIMD away from stuff like standard integer and float operations. Maybe in the early 90s, but they’re such a part of processor design that you can’t realistically avoid them. Especially for rendering, which is matrix math heavy, you’d have to design something completely bespoke to avoid it. SIMD is a natural necessity for rendering with any kind of performance. And because SIMD is such a part of every mainstream processor, it’s very important that benchmarks show how well they perform. I also don’t understand why you think a JavaScript runtime wouldn’t use SIMD. V8 can make use of SIMD, whether directly targeted or indirectly via the compiler that compiled the runtime itself. If you want to stress very specific parts of a processor, then use something like SPEC. Cinebench is meant to be a realistic reflection of production rendering.
    - AnthonyMouse 2y ago
      > Especially for rendering, which is matrix math heavy, you’d have to design something completely bespoke to avoid it. SIMD is a natural necessity for rendering with any kind of performance. Well sure, but rendering is a classically parallel operation which is regularly implemented as threaded. > I also don’t understand why you think a JavaScript runtime wouldn’t use SIMD. V8 can make use of SIMD, whether directly targeted or indirectly via the compiler that compiled the runtime itself. JavaScript runtimes are executing code, so they'll implement the whole gamut and their execution will depend on what kind of code it actually is. But the common JavaScript code, and the kind presumably being tested in JavaScript benchmarks because it's what people care about, isn't implementing a video encoder using SIMD. It's manipulating DOM objects and parsing short pieces of text input, which is branch-heavy code with lots of indirection and very little use of SIMD if any. > If you want to stress very specific parts of a processor, then use something like SPEC. Cinebench is meant to be a realistic reflection of production rendering. Which is kind of my point. Production rendering is going to be threaded and max out all the cores, which is Cinebench MT. "CineBench ST" is measuring something that nobody does in real life and doesn't even really correlate with the things people actually do. It doesn't represent real threaded workloads (which optimally run on many low-clocked cores, not one high-clocked one) nor real serialized workloads (which are full of conditional jumps and cache misses).