Intel have ~85% market share in x86 parts; AMD having the rest. That would seem good except for a quote from that report:
Total MPU shipments decreased 6% quarter-over-quarter in the fourth quarter, well below normal seasonality of down 1% quarter-over-quarter due to slowing PC demand and share loss to tablets. We note microprocessor shipments have now declined sequentially in four of the last five quarters.On the desktop Intel managed to surf the success of Windows & the corresponding demand for x86 parts, so fund the R&D and the Fabs needed to stay ahead of more space efficient RISC CPU architectures. Intel could bring things out like the P5 superscalar CPU with the Pentium, then with the Pentium Pro introduce the first mass market speculative execution CPU architecture, the P6. For these parts and their successors, performance came before power.
The growing performance of those desktop parts not only killed the non-x86 Unix workstation business, they brought the x86 into the server world, pretty much taking a sharp knife to all the Unix on home-rolled CPU business -only IBM's Power and the SPARC lines remain, though how long SPARC will survive remains to be seen. (I'm ignoring Itanium, it being an Intel part too).
That's why when the Hadoop community talks about "commodity" servers, x86 parts are implicit in there. And with 85% market share, that's a lot of CPUs. Or, if you are in networking business, a lot of potentially 10GbE network ports -as nobody else is interested in them.
Intel are supplying the parts for those clusters then, which means they know the number that is selling, and they know something bad about it: most large clusters ship with only one socket filled up.
Problem: Hadoop is usually IO intensive; RAM is often a limiting factor on work. Fill in both sockets and you need to double the RAM too -but even then, may end up idling for data coming off disk or network.
Problem: On the spreadsheets used to cost out a big cluster -you have not only the rows needed to set the parts for each node (ram, storage, CPU), there's one for power. Fill that second socket and not only do you take a CAPEX hit, your OPEX looks worse as your power budget can jump up. And while x86 parts can crank back their wattage when idle, that says "when that second socket you filled is underused, your power bill isn't so bad", as in "If you still overspent on the CAPEX then your OPEX is slightly better".
On a big cluster, not filling that second socket can save enough money you could add another rack of servers -and the storage that comes with it. Storage is a tangible benefit.
Problem: GPUs are where the cycles are coming from, and in HPC clusters, it's worth compiling your code down to it -and working to make sure your code can compile down -and people are exploring GPUs in Hadoop clusters, especially as YARN delivers more cluster flexibility. Intel's attempts to get into the GPU business have failed -apart from the lower power display chipsets used in laptops when they are in battery mode, so GPUs aren't a revenue stream.
Problem on a big datacentre the buyer gets to negotiate prices. This is at its worst (for Intel, AMD, Dell, HP, SuperMicro, SGI) on the big cloud farms, as it will be a take-it-or-leave-it deal for thousands of nodes, and people like Amazon care about both capital cost of parts, and the operational cost of them. The people doing the negotiating know about bill of material curves (see below), and won't be rushing to by the latest part, not if last quarter's part costs significantly less for not much performance difference.
Problem: virtualisation may reduce demand for servers. The more you move to virtual server hosting, the less you need servers for every individual application. The adoption of virtualisation may have driven demand for new blade systems, but now that servers have consolidated, demand may level out -except for the new clusters, HPC racks and cloud service providers.
Problem: The desktop and laptop market are stagnating: the growing end-user products are smart phones and tablets, and with the exception of MS Surface Professional, Intel have barely a presence. Arm owns that market, and AMD have announced their plans to build server-side ARM parts and chipsets. AMD, with only 15% market share, have little to lose after all.
It's not just the CPU design that matters here, it's storage too. As I discussed in my Hadoop Summit EU talk proposal, Hadoop needs to plan ahead here. Tiered storage, many-core WIMPy parts, that's something Hadoop can adopt, especially if we start the groundwork.
And what's part of the nightly Jenkins build of Hadoop? Hadoop on ARM.
There we have it then: Hadoop clusters becoming a big part of the enterprise datacentre, but without demand for CPU parts compared to virtualisation blades and classic HPC systems. GPUs and parts moving from the desktop and ARM cores from the tablet -all have their eyes on the server market, offering massive CAPEX and OPEX savings. Oh, and the desktop market going away while the tablet and phone market remains elusive.
Yes, if you were the premier vendor of today's desktop & server CPUs, you'd be worrying about these -and thinking "even if the desktop business is going down, how can we increase demand for our parts in a growing Hadoop cluster business?"
That can be done in three ways: getting that second socket filled, making sure the CPUs sold have the latest-and greatest parts, and expanding demand for Hadoop clusters.
There is also the SSD business, which is money on the table as far as Intel are concerned: stuff to take from the HDD vendors. There may be competitors -such as Samsung- but if INTC can do mainboards with SSD hooked off the PCIex bus rather than pretending to be disk, there are opportunities that they can exploit.
Finally: 10GbE networking. This is something you need for the latest massive-storage-capacity servers anyway, unless your cluster has so many machines that the loss of single 36TB server isn't significant and the cost of 10GbE switches is. Lower cost of 10GbE switches would be nice.
If you look at the Intel Distribution for Apache Hadoop, then, you can see two features: a justification for multiple CPU sockets filled with the latest parts (encryption using new AES opcodes), and SSD speedup, though not the explicit tiering that the HDFS developers are starting to talk about.
What's not so obvious is why do their own bundling of this, which means they have to take on the entire QA process -which isn't something I've seen in terms of JIRAs filed- and it leaves CPU demand out of mainstream Hadoop. Unless Intel's Hadoop-related product obtains market share rapidly, I'm not sure why they didn't just try and get the CPU-intensive features in early.
[Photo: 3Dom's "The Cycle"; went up on Stokes Croft over the weekend"]