The Intel Xeon E5 v4 Review: Testing Broadwell-EP With Demanding Server Workloads
by Johan De Gelas on March 31, 2016 12:30 PM EST- Posted in
- CPUs
- Intel
- Xeon
- Enterprise
- Enterprise CPUs
- Broadwell
Big Data 101
Many of you have experienced this: you got a massive (text) file (a log of several weeks, some crawled web data) and you need to extract data from it. Moving it inside a text editor will not help you. The text editor will probably collapse and crash as it cannot handle the hundreds of gigabytes of text. Even if it doesn’t, repeated searches (via grep for example) are not exactly a very fast nor are they scientific way to analyze what is hidden inside that enormous hump of data.
Importing and normalizing it into a SQL database via the typical Extract, Transform and Load (ETL) process is tedious and extremely slow. SQL databases are built to handle limited amounts of structured data after all.
That is why Google created MapReduce: by splitting up those massive amounts of data in smaller slices (mapping) and reducing (aggregating, calculating, counting) them to the results that matters to you, you can avoid the rather sequential and slow query execution plans that need to evaluate the whole database to provide meaningful results. Combine this with a redundant and distributed filesystem HDFS that keeps data close to the processing node. The result is that you do not need to import data before you can use it, you do not need the ultimate SSD to quickly load so much data at once, and you can distribute your data mining over a large cluster.
I am of course talking about the grandfather of all Big Data crunching: Hadoop. However Hadoop had two significant disadvantages: although it could crunch through terabytes of data where most other data mining systems collapsed, it was pretty slow the moment you had go through iterative steps, as it wrote the intermediate results to disk. It also was pretty bad if you just want to launch a quick simple query.
Apache Spark 1.5: The Ultimate Big Data Cruncher
This brings us to Spark. In addressing Hadoop’s disadvantages, the members of UC Berkeley’s AMPlab invented a method of keeping the slices of data that need the same kind of operations in memory (Resilient Distributed Datasets). So Spark makes much better use of DRAM than MapReduce, and also avoids many write operations.
But there is more: the Spark framework also includes machine learning / AI libraries that you can use inside your scala/python code. The resulting workload is a marriage of machine learning and data mining that is highly parallel and does not need the best I/O technology to crunch through hundreds of gigabytes of data. In summary, Spark absolutely craves more CPU power and better RAM technology.
Meanwhile, according to Intel, this kind of big data technology is top growth driver of enterprise compute demand in the next few years, as enterprise demand is expected to grow by 67%. And Intel is not the only one that has seen the opportunity; IBM has a Spark Technology Center in San Francisco and launched "Insight Cloud Services", a cloud service based on top of Spark.
Intel now has a specialized Big Data Solutions group, led by Ananth Sankaranarayanan. This group spearheaded the "Big Bench" benchmark development, which was adopted by a TPC group as TPCx-BB. The benchmark is expressed in BBQs per minute...(BBQ = Big Bench Queries). (ed: yummy)
Among the contributors are Cloudera, Cisco, VMware and ... IBM and Huawei. Huawei is the parent company of the HiSilicon ARM processor, and IBM of course has the POWER 8. Needless to say, the new benchmark is going to be an important battleground which might decide whether or not Intel will remain the dominant enterprise CPU vendor. We have yet to evaluate TPC-BBx, but the next page gives you some hard benchmark numbers.
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JohanAnandtech - Saturday, April 2, 2016 - link
Ok, thanks, time to sleep a little longer. I have fixed the error.xrror - Friday, April 1, 2016 - link
It's depressing to see the mobile-first design philosophy really gutting into the last bastion of x86 performance.I mean I get it - a 22 (20) core xeon wouldn't even exist without the aggressive power management tech needed to keep it from melting or needing exotic cooling. But it's still depressing to see ALL of the arch improvements immediately negated with lowered clock speeds, or worse "turbo speeds" you will never actually see once the machine is running production loads.
The engineering behind these big core count chips though is always very impressive. Also did Intel ever say how they "fixed" TSX?
FunBunny2 - Friday, April 1, 2016 - link
"It's depressing to see the mobile-first design philosophy really gutting into the last bastion of x86 performance."welcome to the world of laissez faire capitalism: do what makes the most money today, irregardless of future consequences. used to be, Intel could rely on M$ making the next versions of Windoze and Office impossible to run on existing Pentiums, thus driving sales of the next Pentium (a whole machine, at that). these days it's up to gamers and data centres. not taking any bets on which turns out to be in the driver's seat.
xrror - Friday, April 1, 2016 - link
Well, considering that "computer gaming" has degraded to whatever the kids are running on their smartphones, or the parent's tablet I'm not hopeful for any new resurgence in demand for high performance PC's in the mass market.So the future consequences for Intel prioritizing power efficiency over performance, or possibly developing a separate fabrication tech for performance is... likely not very much. So there really is no "future consequence" for Intel. Sure they could go out and actually try and make a 10Ghz 9nm part possible, but nobody in 2020 would buy it because... it probably would go into whatever iDevice they care about. And HPC market I dunno. Maybe if it datamines marketing data faster or can microtrade on the stock market faster or something. meh.
The general public really doesn't care about performance anymore (honestly, they may never have), only how portable it is and if a device is good enough to run their stuff on the go.
The high end market like these multi-core xeons though, is strange because you'd think this is where Intel would go all in, but I guess when your only competitors are IBM Power and (currently non-competitive) AMD I dunno...
I mean it's sad, even Intel has to beg to justify it's R&D expenses to shareholders - which is stupid because Intel's R&D is one of it's biggest strengths. But such as it is. Apr 1 rant over ;)
abufrejoval - Friday, April 1, 2016 - link
Johan, you keep bemoaning the fact that lack of competition seems to stop "real progress" and I wonder where you expect that progress to happen.More specifically you seem to desire more GHz and I can understand that desire, which may originate from that crazy 40MHz to 4GHz rush we all experienced somewhere in the decade starting in the mid nineties.
I understand the emotion, but I wonder how it fits the scientific mind I see everywhere else in your work, because 8, 16 or 32 GHz is simply not going to happen, competition or not.
Sure 8GHz are possible, you can even purchase 5GHz off the shelves. But it simply doesn't deliver in terms of Oomp/$. And Web Scale is all about value/€ and the main driver of server evolution today.
We'll still see radical speedups where it counts, but it will have to be via special purpose function blocks either on SoCs, or by adding a couple of extra instructions or by doing something as radical as Micron's Automata Processor.
But general purpose von Neumann has hit the Gigahertz wall years ago and nothing can change that except a different model of compute.
I liked the reference to Andreas Stiller, but I'm not sure everybody here has a subscription to c't like I do since the early 1990's. There could also be the tiny issue that not everyone outside Belgium is quadrilingual.
Make no mistake: I love your work! It's a pleasure to read for form, style and the content!
The Von Matrices - Saturday, April 2, 2016 - link
Any indication of the QPI speed of these chips? Did Intel increase it from the 9.6 GT/s in Haswell-EP?Ian Cutress - Saturday, April 2, 2016 - link
Most of the high end are 9.6 GT/s. https://twitter.com/IanCutress/status/715582714099...watersb - Saturday, April 2, 2016 - link
Johan, this is fantastic work. Thanks very much.Any way to address RAS features?
isrv - Saturday, April 2, 2016 - link
well, i'm completely dissapointed.web servers wants higher clock speed.
single-thread load (like PHP) become even slower on those E5v4 due to drop in GHz's.
still, the best CPU's for that is E3-1290v2, E3-1281v3 (and 1286v3), E3-1280v5, E5-1630v3, E5-1620v2 and the only one 6-core E5-1660v2
all those are 3.7Ghz (pointless to look at turbo speed since we're under constant 24/7 load).
i was hoping to at least one 3.8GHz or even higher.
so no changes here, E5-1660v2 is still the fastest web-server CPU.
or E5-1630v3 by sacrificing 2 cores for a bit faster memory.
patrickjp93 - Sunday, April 3, 2016 - link
For those 4-8 core chips, the turbo boost is maintainable for 24/7 workloads if your cooling is sufficient. You seem to know far less about this environment than you let on. And who the hell still uses single-threaded PHP? And you're not taking into account better caching algorithms and other architectural improvements that make the 200MHz slower V4 run faster than your V2.