As part of this review, we also ran our normal motherboard benchmarks.

WinRAR x64 3.93 - link

With 64-bit WinRAR, we compress the set of files used in the USB speed tests. WinRAR x64 3.93 attempts to use multithreading when possible, and provides as a good test for when a system has variable threaded load.  If a system has multiple speeds to invoke at different loading, the switching between those speeds will determine how well the system will do.

WinRar x64 3.93

WinRAR is another example where enabling HyperThreading is actually hurting the throughput of the system. But even with all 32 threads in the system, the lack of memory speed hurts the benchmark.

FastStone Image Viewer 4.2 - link

FastStone Image Viewer is a free piece of software I have been using for quite a few years now.  It allows quick viewing of flat images, as well as resizing, changing color depth, adding simple text or simple filters.  It also has a bulk image conversion tool, which we use here.  The software currently operates only in single-thread mode, which should change in later versions of the software.  For this test, we convert a series of 170 files, of various resolutions, dimensions and types (of a total size of 163MB), all to the .gif format of 640x480 dimensions.

FastStone Image Viewer 4.2

FastStone is relatively unaffected due to the single-threaded nature of the program.

Xilisoft Video Converter

With XVC, users can convert any type of normal video to any compatible format for smartphones, tablets and other devices.  By default, it uses all available threads on the system, and in the presence of appropriate graphics cards, can utilize CUDA for NVIDIA GPUs as well as AMD APP for AMD GPUs.  For this test, we use a set of 33 HD videos, each lasting 30 seconds, and convert them from 1080p to an iPod H.264 video format using just the CPU.  The time taken to convert these videos gives us our result.

Xilisoft Video Converter 7

With XVC having many threads is what wins the day, and having HT enabled made the process very fast indeed.  With HT on, we have 32 threads, meaning most of the videos were actually converted very quickly – the final 33rd video caused an extra delay at the end.  This is yet another example of an algorithm that can be ported to GPUs, as XVC offers both an AMD and NVIDIA option for conversion.

x264 HD Benchmark

The x264 HD Benchmark uses a common HD encoding tool to process an HD MPEG2 source at 1280x720 at 3963 Kbps.  This test represents a standardized result which can be compared across other reviews, and is dependant on both CPU power and memory speed.  The benchmark performs a 2-pass encode, and the results shown are the average of each pass performed four times.

x264 HD Pass 1

x264 HD Pass 2

In contrast to XVC, which splits its threads across many files, the x264 HD benchmark splits threads across one file.  As a result it seems that having HT off gives a subtle 13.7% boost in performance in the first pass and 11.0% boost in the second pass.  The results of the first pass makes the second pass a lot more efficient across all the threads due to fewer memory accesses.

n-Body Simulations System Benchmarks
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  • Hulk - Saturday, January 05, 2013 - link

    I had no idea you were so adept with mathematics. "Consider a point in space..." Reading this brought me back to Finite Element Analysis in college! I am very impressed. Being a ME I would have preferred some flow models using the Navier-Stokes equations, but hey I like chemistry as well. Reply
  • IanCutress - Saturday, January 05, 2013 - link

    I never did any FEM so wouldn't know where to start. The next angle of testing would have been using a C++ AMP Fluid Dynamics Simulation and adjusting the code from the SDK example like with the n-Body testing. If there is enough interest, I could spend a few days organising it for the normal motherboard reviews :)

    Ian
    Reply
  • mayankleoboy1 - Saturday, January 05, 2013 - link

    How the frick did you get the i7-3770K to *5.4GHZ* ? :shock:
    How the frick did you get the i7-3770K to *5.0GHZ* ? :shock:
    Reply
  • IanCutress - Saturday, January 05, 2013 - link

    A few members of the Overclock.net HWBot team helped testing by running my benchmark while they were using DICE/LN2/Phase Change for overclocking contests (i.e. not 24/7 runs). The i7-3770K will go over 7 GHz if (a) you get a good chip, (b) cool it down enough, and (c) know what you are doing. If you're interested in competitive overclocking, head over to HWBot, Xtreme Systems or Overclock.net - there are plenty of people with info to help you get started.

    Ian
    Reply
  • JlHADJOE - Tuesday, January 08, 2013 - link

    The incredible performance of those overclocked Ivy bridge systems here really hammers home the importance of raw IPC. You can spend a lot of time optimizing code, but IPC is free speed when it's available. Reply
  • jd_tiger - Saturday, January 05, 2013 - link

    http://www.youtube.com/watch?v=Ccoj5lhLmSQ Reply
  • smonsees - Saturday, January 05, 2013 - link

    You might try modifying your algorithm to pin the data to a specific core (therefore cache) to keep the thrashing as low as possible. Google "processor affinity c++". I will admit this adds complexity to your straightforward algorithm. In C#, I would use a parallel loop with a range partition to do it as a starting point: http://msdn.microsoft.com/en-us/library/dd560853.a... Reply
  • nickgully - Saturday, January 05, 2013 - link

    Mr. Cutress,
    Do you think with all the virtualized CPU available, researchers will still build their own system as it is something concrete to put into a grant application, versus the power-by-the-hour of cloud computing?

    Thanks.
    Reply
  • IanCutress - Saturday, January 05, 2013 - link

    We examined both scenarios. Our university had cluster time to buy, and there is always the Amazon cloud. In our calculation, getting a 16 thread machine from Dell paid for itself in under six months of continuous running, and would not require a large adjustment in the way people were currently coding (i.e. staying in Windows rather than moving to Linux), and could also be passed down the research group when newer hardware is released.

    If you are using production level code and manipulating it each time to get results, and you can guarantee the results will be good each time, then power-by-the-hour could work. As we were constantly writing and testing new code for different scenarios, the build/buy your own workstation won out. Having your own system also helps in building GPU codes, if you want to buy a better GPU card it is easier to swap out rather than relying on a cloud computing upgrade.

    Ian
    Reply
  • jtv - Sunday, January 06, 2013 - link

    One big consideration is who the researchers are. I work in x-ray spectroscopy (as a computational theorist). Experimentalists in this field use some of our codes without wanting to bother with having big computational resources. We have looked at trying to provide some of our codes through some cloud-based service so that it can be used on demand.

    Otherwise I would agree with Ian's reply. When I'm improving code, debugging code, or trying to implement new theoretical approaches I absolutely want my own hardware to do it on.
    Reply

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