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  1. J

    Apple A9X the new mobile SoC king

    Only on Apple platforms, though. Other platforms don't have an equivalent to Accelerate.
  2. J

    Apple A9X the new mobile SoC king

    q1 2016. :)
  3. J

    Apple A9X the new mobile SoC king

    SGEMM and DGEMM take advantage of SSE and NEON. Geekbench 4 will be built with Visual Studio 2015 on Windows.
  4. J

    Apple A9X the new mobile SoC king

    The desktop dataset is too large for mobile devices -- it does not fit onto mobile devices with less than 1GB of RAM. Even if it did fit, the runtime would be unreasonably long for our users. The mobile dataset it too small for desktop devices -- execution times would become small enough...
  5. J

    Apple A9X the new mobile SoC king

    Geekbench 3 takes advantage of SIMD instructions for some of the workloads. We build Geekbench with the de-facto standard compiler for each platform since this how most software is built. I'm not aware of any platforms where the Intel compiler is used for a non-trivial amount of software...
  6. J

    Apple A9X the new mobile SoC king

    FWIW, here's a comparison between the mobile and desktop workload sizes on the A9: http://browser.primatelabs.com/geekbench3/compare/3594692?baseline=3594646 Mobile is on the left, desktop is on the right.
  7. J

    Apple A9X the new mobile SoC king

    When Geekbench 3 was released, there was a huge delta between desktop and mobile performance. Running the desktop dataset on mobile devices would increase runtimes to a point where our users would become impatient. Running the mobile dataset on desktops would decrease runtimes to a point where...
  8. J

    Apple A9X the new mobile SoC king

    For Geekbench 3 append ".gb3" to URLs to download the raw JSON result, which you can then parse with our Python scripts: https://github.com/primatelabs/geekbench-tools/tree/master/geekbench3
  9. J

    Samsung Exynos Thread (big.LITTLE Octa-core)

    Huh! Thanks for the heads up.
  10. J

    [AT] NVIDIA Denver performance

    We're reading the maximum frequency from /sys/devices/system/cpu/cpu0/cpufreq/cpuinfo_max_freq (which is 2499000 on a Nexus 9). /sys/devices/system/cpu/cpu0/cpufreq/stats/time_in_state shows that the device never goes beyond 2295 MHz, though: shell@flounder:/ $ cat...
  11. J

    [AT] NVIDIA Denver performance

    What about this? The Mediatek MT6577 has two A9 cores: http://browser.primatelabs.com/geekbench3/compare/1191919?baseline=1191643
  12. J

    [AT] NVIDIA Denver performance

    We've put a lot of effort into making sure cross-platform comparisons are valid. Using Geekbench 3 to compare iOS and Android devices is quite valid. Recent iOS devices do quite well in Geekbench 3 for two reasons: * A7, A8, and A8X chips have impressive processor cores. * A7, A8, and A8X...
  13. J

    [AT] NVIDIA Denver performance

    Could you let me know of scenarios where we report the wrong frequency? I'm aware of an issue with big.LITTLE systems but otherwise Geekbench should report the correct frequency under Android.
  14. J

    Core M v.s. A8X in Geekbench 3

    This is a toolchain limitation. Dijkstra's data structures contain a lot of pointers, so it's a combination of increased memory transfer and increased cache pressure. I don't know why BZip2 Decompress is faster off the top of my head. I believe Clang performs the same optimization, which...
  15. J

    Core M v.s. A8X in Geekbench 3

    Only the AES and SHA-1 workloads show an improvement on AArch32 (thanks to the ARMv8 cryptography instructions). AArch32 doesn't include the extra registers or the double-precision NEON instructions that are part of AArch64.
  16. J

    Core M v.s. A8X in Geekbench 3

    AArch32 is ARMv7+Crypto (plus a handful of new NEON instructions).
  17. J

    Core M v.s. A8X in Geekbench 3

    Sounds good. We won't be able to incorporate any feedback into Geekbench 3 (we want to keep v3 scores as comparable as possible) but we'll certainly consider incorporating your feedback for v4.
  18. J

    Core M v.s. A8X in Geekbench 3

    Geekbench's GEMM workloads weren't written to measure peak performance, they were written to measure relative performance. Take a look at the performance of Geekbench's GEMM implementation compared to Accelerate's GEMM implementation on both x86 and ARM: Apple A8 @ 1.4 GHz SGEMM...
  19. J

    Core M v.s. A8X in Geekbench 3

    Our plan is to automate as much as possible. During development the workloads change too much for a manually-verified baseline to remain relevant for more than a couple of days. Once the workloads are stable, though, a baseline will be useful.
  20. J

    Core M v.s. A8X in Geekbench 3

    iPhone 5s 32-bit result: http://browser.primatelabs.com/geekbench3/1073639 iPhone 6 32-bit result: http://browser.primatelabs.com/geekbench3/1073585 We should have an iPad Air 2 in the office later this week.
  21. J

    Core M v.s. A8X in Geekbench 3

    Please do! Note, though, that the GEMM kernel in the blog post is a simplified kernel designed to illustrate the compiler issue we encountered with Visual C++ and is different from the actual GEMM kernel that ships with Geekbench 3. The actual kernel may address issue #1 (don't thrash the...
  22. J

    Core M v.s. A8X in Geekbench 3

    ARMv8 has instructions for SHA-1 and SHA-2 (SHA-256). Geekbench 3 only uses the ARMv8 instructions for the SHA-1 test (SHA-2 is a straightforward-ish software implementation). IIRC ARMv8 SHA-1 is 4x faster than C++ SHA-1 on the A8. Happy to post 32-bit results for the A7, A8, and A8X if...
  23. J

    Core M v.s. A8X in Geekbench 3

    That's our expectation as well. This approach won't help with bugs in the "backend" of the compiler (e.g., code generation) for architectures that aren't part of the automated system. Our goal for v4 is to have the automated system cover all of the architectures we ship so that we won't have...
  24. J

    Core M v.s. A8X in Geekbench 3

    Anthony's post only covered the automated system he developed for Geekbench 3 which (at the time) was limited to x86 platforms. It didn't cover any of the manual work we did during development. What's great about the automated system is that it makes detecting cross-platform (or...
  25. J

    Apple A8x

    It's easy to spoof Geekbench on Android, but it's tricky to spoof on iOS. I'm convinced the 3-core iPad Air result is legitimate.
  26. J

    Apple A8x

    Saying that no Geekbench test is indicative of real-world usage is not fair or reasonable. While some of the tests in Geekbench 3 are synthetic tests (Mandelbrot and STREAM being the prime examples) most of the tests either use libraries (e.g., JPEG, Lua) or algorithms (e.g., Dijkstra, FFT)...
  27. J

    Apple A8x

    Nothing yet! This search should show the A8X results when finally arrive on the Geekbench Browser: http://browser.primatelabs.com/geekbench3/search?q=ipad5
  28. J

    Apple A8x

    Geekbench 3 SHA-1 and SHA-2 workloads operate on a single data buffer because we don't believe cryptographic hashes operating on multiple data buffers is representative of real-world usage.
  29. J

    Apple A8 Benchmarked

    I wonder if the hardware JPEG encoder is built in such a way that it's only available to the camera (i.e., it's a tightly integrated part of the RAW to JPEG pipeline in the camera with no external interface)? That would explain why people are asking about it without much luck.
  30. J

    Apple A8 Benchmarked

    Thank you for the pointer! I took a quick look through the Android 4.4 source code and found that the Android graphics library uses libjpeg to decode JPEG images. This is the same library Geekbench 3 uses for its JPEG workloads. Maybe the hardware JPEG acceleration referenced in the article...
  31. J

    Apple A8 Benchmarked

    Geekbench 3 only uses "dedicated hardware" for the AES and SHA-1 workloads. I wouldn't expect the other workloads (with the exception of SHA-2) to be accelerated by dedicated hardware in real-world scenarios. For example, I would expect JPEG compression and decompression to happen in software...
  32. J

    The Intel Atom Thread

    Geekbench takes advantage of AES-NI on Silvermont.
  33. J

    Surreptitious Samsung Benchmark Shenanigans

    I've heard (but have been unable to verify) that these shenanigans also raise the thermal limits of the processor. So not only will all CPU cores start out at peak frequency when running benchmarks, they'll run at peak frequency for longer (before throttling down due to thermal limits) when...
  34. J

    Apple A7 is now 64-bit

    Using Clang with the NDK is pretty straightforward, and I'm not aware of any major Clang-specific NDK issues. I believe it took us less than an hour to switch our Android build from GCC to Clang, and everything Just Worked after the switch. That said, we did see a performance drop after...
  35. J

    Geekbench 3 Sandy Bridge v.s. Apple Cyclone IPC comparison

    We haven't seen any evidence that suggests Clang's ARM code generation is ahead of GCC's x86 code generation in the way that ICC's x86 code generation is significantly ahead of GCC's x86 code generation. We also haven't seen any evidence that suggests Clang engages in any "benchmark...
  36. J

    Geekbench 3 Sandy Bridge v.s. Apple Cyclone IPC comparison

    The Geekbench 3 SHA-2 workload only operates on a single buffer of data, while some of the SiSoft Sandra SHA-2 workloads operate on multiple buffers of data at the same time using vector instructions. I don't have a copy of SiSoft Sandra handy, but according to this page their "single-buffer"...
  37. J

    Benchmark your Computer with the New Geekbench 3

    Geekbench 3 for Windows is built with Visual C++ 2012 Update 2. Geekbench 3 for OS X, Linux are built with Clang 3.3. I'm not sure where the "Intel-only" paths are coming from in the executable. We'll dig into it and I'll post here once we've figured it out.
  38. J

    AnTuTu and Intel

    All of the memory workloads will be multi-threaded in v3. The biggest difference is on multi-socket systems, but we've even seen a boost on some Android and iOS handsets.
  39. J

    Intel Z3770 geekbench sighted

    I've uploaded a simple script (geekbench-recalculate.py) to our Geekbench tools repo that makes this easy: https://github.com/primatelabs/geekbench-tools/ Just point the script at the URL of the result you want to recalculate and it'll do the rest. Right now the script just excludes the...
  40. J

    Intel Z3770 geekbench sighted

    If you've got a minute I'd be really interested to hear what these doubts are so that we can improve the workload for v3.
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