Integer Processing

To measure the integer processing potential of the various CPUs, we'll turn to several different workloads. First up, we have 7z LZMA compression and decompression, again looking at performance with one to four threads. On the next page, we'll look at gcc compiler performance.


Compression is a low IPC workload that's sensitive to memory parallelism and latency. The instruction mix is a bit different, but this kind of workload is still somewhat similar to many server workloads.

LZMA Compression- 1 to 4 threads

Clock for clock, the out-of-order Cortex-A9 inside the Calxeda EXC-1000 beats the in-order Atom core. A single Cortex-A9 has no trouble beating the older Atoms while likewise coming close to the much higher clocked N2800. The N2800 and ECX-1000 perform similarly.


Decompression is pretty branch intensive and depends on the latencies of multiply and shift instructions.

7z LZMA Decompression- 1 to 4 threads

Branch mispredictions are common and the Atom tackles branch mispredictions well with its Simulteanous MultiThreaded (SMT) core. The boost from Hyper-Threading is very large here: a second ARM Cortex-A9 core gives a 52% boost and Hyper-Threading gives a 56% boost. This is very much the exception as far as Hyper-Threading performance is concerned.

Looking at both decompression and compression, it looks like a quad ARM Cortex-A9 is about as fast as one Xeon core (without Hyper-Threading) at the same clock. We need about six Cortex-A9 cores to match the Xeon core with Hyper-Threading enabled. The quad-core ECX-1000 1.4GHz is also close to the dual-core, four-threaded Atom at 1.86GHz. This bodes well for Calxeda as the 6.1W S1240 only runs at 1.6GHz.

Measuring Bandwidth Integer Processing, gcc
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  • JohanAnandtech - Wednesday, March 13, 2013 - link

  • SunLord - Wednesday, March 13, 2013 - link

    Hmm if these didn't cost $20,000 they would make a nice front end for larger websites and forums using less rack space and power. What setup using these would you use for anandtech? Would you guys keep the intel DB server?
  • Gunbuster - Wednesday, March 13, 2013 - link

    I just got a Dell R720xd decked out with 384GB and 4.3TB of storage for a hair over that price.
  • JohanAnandtech - Wednesday, March 13, 2013 - link

    Intel Xeons are still by far a better choice for relational databases that are very hard to split up (sharding is only a last resort)
  • zachj - Wednesday, March 13, 2013 - link

    I'm not sure I agree with the absolutism that seems imlicit in your comment that Xeons are better for relational databases...I think there are cases where that won't be true.

    Database scale-out doesn't always require sharding...using any of a number of different off-the-shelf capabilities built right into most SQL engines, you can create multiple active replicas of your database. This is generally better-suited to workloads that aren't write-intensive, but both clustering and replication allow for writes. While this may seem like a quick-and-dirty solution that is architecturally "less good" than sharding, hardware is a lot cheaper than paying people to design a sharding solution and the dollars very often drive the conversation. As long as the database size isn't terribly large this can be a very cost-effective way to scale out a database.

    I would wager that the Anandtech website database (not the forum database) would probably be well-suited to this type of scale-out. You do waste some money on redundant storage but you more than make up for that cost by not having to pay a development team to implement sharding. If the comments section of the Anandtech website gets stored in the same underlying database, the size constraints and the write activity may appear to be incompatible with this approach, but I would in fact argue that comments don't require relational capabilities of SQL and would be more rightly stored as blobs in Hadoop or Azure Storage Tables. Then the Anandtech database is strictly articles and is both much more compact and almost entirely read-only (except for a few new articles per day).
  • rwei - Friday, March 15, 2013 - link

    To the best of my understanding, replication does well for scaling reads but doesn't do much for writes. I'd still imagine that this would work decently well with AnandTech, where I can't see the volume of writes being that large relative to the volume of reads.
  • Kurge - Wednesday, March 13, 2013 - link

    They would make a horrible front end for such websites. Just buy a single Xeon server and don't artificially limit it by using 24 VMs. Just run the app straight on the metal and it will perform massively better.
  • Oldboy1948 - Wednesday, March 13, 2013 - link

    Very interesting Johan as your tests often are!
    Interesting that the memory bw is so much lower than anything from Intel. In fact Iphone 5 looks much better...why? Only Intel has about the same rsults in compress and decompress.
  • JohanAnandtech - Wednesday, March 13, 2013 - link

    Where did you see the stream results on the A6? I might have missed it somewhere. The only ones I could find reported only 1 GB/s in Triad. The Quad ECX-1000 got 1.8 GB/s
  • PCTC2 - Wednesday, March 13, 2013 - link

    Do you know what would be an interesting concept for a future version of these cluster-in-a-box systems? A solution like ScaleMP. ScaleMP is basically a reverse VM. A hypervisor on each server clusters together to run a single OS with an aggregation of all resources (cores, RAM, network, and disk). ScaleMP running on 4x Dual-socket 8-core Xeon systems w/ 32GB RAM results in a usable system with 64-cores and 128GB RAM as if it was running natively on the hardware. This would be an interesting concept to transfer to the ARM space (if a form of hardware virtualization ever is designed). In a box like this, there would be 192 cores and 192GB of RAM available to a single Fedora instance. Cluster 2 of these together and suddenly there's a system with 384 cores and 384GB of RAM in 4U. Just some food for thought.

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