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NVIDIA Announces Tesla K40 GPU Accelerator and IBM Partnership In Supercomputing
MojoKid writes "The supercomputing conference SC13 kicks off this week and Nvidia is kicking off their own event with the launch of a new GPU and a strategic partnership with IBM. Just as the GTX 780 Ti was the full consumer implementation of the GK110 GPU, the new K40 Tesla card is the supercomputing / HPC variant of the same core architecture. The K40 picks up additional clock headroom and implements the same variable clock speed threshold that has characterized Nvidia's consumer cards for the past year, for a significant overall boost in performance. The other major shift between Nvidia's previous gen K20X and the new K40 is the amount of on-board RAM. K40 packs a full 12GB and clocks it modestly higher to boot. That's important because datasets are typically limited to on-board GPU memory (at least, if you want to work with any kind of speed). Finally, IBM and Nvidia announced a partnership to combine Tesla GPUs and Power CPUs for OpenPOWER solutions. The goal is to push the new Tesla cards as workload accelerators for specific datacenter tasks. According to Nvidia's release, Tesla GPUs will ship alongside Power8 CPUs, which are currently scheduled for a mid-2014 release date. IBM's venerable architecture is expected to target a 4GHz clock speed and offer up to 12 cores with 96MB of shared L3 cache. A 12-core implementation would be capable of handling up to 96 simultaneous threads. The two should make for a potent combination."
"Mantle", at least according to the press puffery, is aimed at being an alternative to OpenGL/Direct3d, akin to 3DFX's old "Glide"; but for AMD gear.
CUDA vs. OpenCL seems to be an example of the ongoing battle between an entrenched and supported; but costly, proprietary implementation, vs. a somewhat patchy solution that isn't as mature; but has basically everybody except Nvidia rooting for it.
"Mantle", like 'Glide' before it, seems to be the eternal story of the cyclical move between high-performance/low-complexity(but low compatibility) minimally abstracted approaches, and highly complex, highly abstracted; but highly portable/compatible approaches. At present, since AMD is doing the GPU silicon for both consoles and a nontrivial percentage of PCs, it makes a fair amount of sense for them to offer a 'Hey, close to the metal!' solution that takes some of the heat off their drivers, makes performance on their hardware better, and so forth. If, five years from now, people are swearing at 'Mantle Wrappers' and trying to find the one magic incantation that actually causes them to emit non-broken OpenGL, though, history will say 'I told you so'.
I wouldn't say that's strictly true - Mavericks implements OpenCL 1.2 support pervasively, even down to the rinky-dink Intel GPUs that can handle it.
IBM has announced willingness to license the Power8 design in much the same way that ARM licenses their stuff to a plethora of companies. IBM has seen what ARM has accomplished at the lower end in terms of having relevance in a market that might otherwise have gone to Intel given sufficient time, and sees motivation to do that in the datacenter where Intel has significantly diminished POWER footprint over the years. Intel operates at obscene margins due to the strength of their ecosystem and technology, and IBM is recognizing that it needs to build a more diverse ecosystem itself if it wants to compete with Intel. That and the runway may be very short for such an opportunity. ARM as-is is not a very useful server platform, but that gap may close quickly before IBM can move, particularly as 64-bit ARM designs start getting more prevalent.
For nVidia, things are a bit more than 'sure we'll take more money'. nVidia spends a lot of resources on driver development and without their cooperation, using their GPU accelerator solution will get nowhere. nVidia has agreed to invest the resources to actually support Power. Here, nVidia is also feeling the pressure from Intel. Phi has promised easier development for accelerated workloads as a competitor to nVidia solutions. As yet, Phi hasn't been everything people had hoped for, but the promise of easier development today and promise for improvements later has nVidia rightly concerned about future opportunities in that space. Partnering with a company without such ambitions gives them a way to try to apply pressure against a platform that clearly has it's sights on closing the opportunity for GPU acceleration in HPC workloads. Besides, IBM has the resources to help give a boost in terms of software development tooling that nVidia may lack.
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