5 ms·
My question is what market is going to be driving this? Who will want to buy this, and how deep are their pockets? Is this a niche product for a handful of ap
by csense 11y ago
My question is what market is going to be driving this? Who will want to buy this, and how deep are their pockets? Is this a niche product for a handful of applications, or something we'll see in every PC in 5 years?
The GPU was successful because it had a killer app: Gaming. What's the killer app for the FPGA going to be?
- sapek 11y agoSome public information on what MSFT is doing today: http://research.microsoft.com/en-us/projects/catapult/ http://research.microsoft.com/en-us/projects/catapult/
- extrapickles 11y agoServer side things. Machine learning, on cpu die network switch, various forms of offloading (SSL, compression, possibly hypervisor stuff). It will be awhile before it shows up in consumer gear, as the use cases are not there yet. Consumers may still benefit as when someone figures out something amazing for it to do, they will get a hardened version of it.
- creshal 11y ago> various forms of offloading (SSL, compression, possibly hypervisor stuff). I wonder whether Intel will allow that. Better hardware offloading for various algorithms (SHA, RSA, AES, …) and hypervisor acceleration (VT-x, VT-d, EPT, APICv, GVT, VT-c, SRIOV, …) have been one of the main selling points for new CPU generations. An FPGA would render most of them moot by allowing operators to configure whatever offloading they need without requiring new, expensive Intel chips.
- sklogic 11y agoMaybe they will market their next generations as "bigger and better FPGAs" now.
- extrapickles 11y agoIntel can always release versions with more fabric, better access to the cores, main memory, caches and system devices. It will also open up the ability for them to separately sell offloading features as IP cores. Also the risk of them having to disable a feature because of an error goes down as they can easily issue an update for it.
- wtallis 11y agoThe virtualization stuff isn't offloadable. They're a bunch of invasive changes to the memory and I/O paths of the processor core, not stuff that could be handed off to a coprocessor.
- Dylan16807 11y agoYou could route a lot of the I/O paths through the FPGA if it was suitably wired. A slight latency bump to make aspects of virtualization never require any cycles to be spent handling them.
- oakwhiz 11y agoThey can always sign the FPGA bitstreams so that only approved bitstreams are allowed to run on matching approved silicon. Similar to CPU binning, certain CPUs would only be able to load certain bitstreams depending on fuse flags.
- kryptiskt 11y agoCustom circuitry will always be much more efficient than the same thing on an FPGA, so it should be easy to outcompete the FPGA for a task. The FPGA can help Intel with market research for what to put in silicon, just look at what is popular to put there.
- petra 11y agoToday's FPGA's take maybe 10x-20x more chip area, hence much more expensive than the same logic implemented in an ASIC,Same goes with power, so selling FPGA's would be more profitable in and of itself, plus having a full ecosystem doing r&d on FPGA algorithms which Intel can later build into chips and sell.
- nitrogen 11y agoAnything reasonably parallel that needs high throughput or low latency can benefit from an FPGA. I would probably find use for one in audio/video processing offload for media production. If the FPGAs entered consumer parts, games could use them for I/O offloading to give gamers a latency edge, or process thousands of parallel game simulation elements in ways maybe GPUs can't help.
- adwn 11y ago> Anything reasonably parallel that needs high throughput or low latency can benefit from an FPGA. That is not quite right. Rather: "Anything reasonably parallel that needs high throughput or low latency and which is not already provided by the CPU or GPU can benefit from an FPGA." Modern server and desktop CPUs are incredibly fast and offer a lot of parallelism for certain operations. For example, when it comes to floating-point operations, no FPGA has the slightest chance against a desktop CPU (for prices in the same order of magnitude), and even less against a GPU.
- sklogic 11y agoCPUs and GPUs got a pathetic memory bandwidth. For this class of problems FPGAs are unmatched.
- adwn 11y agoAre you refering to internal bandwidth? Because CPUs have roughly the same external memory bandwidth, and GPUs have about an order of magnitude higher external bandwidth than FPGAs.
- sklogic 11y agoBoth internal and external. The larger FPGA parts can host quite lot of DDR controllers, but what is the most important thing here is that there are HUNDREDS of single-cycle two-port block rams. No CPU or GPU can match this with their pitiful fixed tiny caches.
- kbob 11y agoMicrosoft and (apparently) Intel think the killer app is in accelerating datacenter apps. I think it's more likely to be something nobody is doing yet.
- crmd 11y agoStorage - compression
- Ericson2314 11y agoWhile I've messed around with FPGAs alone and found it fun, anything I imagine them doing as an accelerator/coprocessor/whatever sounds quite dull. The program to reprogram them every few seconds (genetic algorithms?) sounds more interesting.
- imtringued 11y agoIf you don't need it as an accelerator then what is the point of hardware FPGA? Just use a simulator in that case.
- berntb 11y agoCould you design a language which do a JIT style compilation to data flow calculations, by creating some arithmethic and logical functions onto a FPGA? (I assume the FPGA would need a way to take over the computer bus and access memory? How multiple functional FPGA subunits do that, I leave as an exercise for Intel. :-) ) A dynamic software accelerator, not a specific function one. (It is probably obvious from the above that the little I know of hardware and FPGAs is a bit old... we almost used keyboards made out of stone. :-) )
- adwn 11y ago> Could you design a language which do a JIT style compilation to data flow calculations, by creating some arithmethic and logical functions onto a FPGA? The complete compilation process (source code --> netlist --> mapped design --> placed & routed design) can take several hours for large designs; maybe several minutes for small designs. Not suitable for JIT.
- Ericson2314 11y agoIt was for school. Simulator would have worked fine.
- Natanael_L 11y agoCustom full disk encryption implementations, like crypto acceleration for an algorithm such as norx.io. Or custom video codec acceleration for streaming it rendering. Or physics simulation acceleration.
- adwn 11y ago> Or physics simulation acceleration. No: Physics simulations are typically FLOPS-limited; modern CPUs deliver a lot more floating-point operations per second than FPGA devices at comparable prices.
- leni536 11y agoCan't one trade precision to do fast fixed point operations on FPGAs?
- adwn 11y agoIt's not only the precision (i.e., the bit-width), but also the variable exponent (i.e., the "floating-point" part). Unfortunately, simulations often cover a wide range of exponents during a single run (one matrix element might be 5.74293574325e8, while the one next to it might be 3.25356343e-9, and you still want to preserve their precision), and the exponents of the inputs might vary a lot between different runs. You can only use fixed-point if you have a good idea of the exponents of the input numbers, and how those change during the course of the computation. That works well for typical digital signal processing applications, and not so well for generic number crunching libraries.
- vonmoltke 11y ago> That works well for typical digital signal processing applications, and not so well for generic number crunching libraries. Even then it breaks down with more complex signal processing algorithms. FPGAs are great for simpler algorithms like FFTs, digital filtering, and motion compensation. They aren't quite as good at more complicated algorithms like edge detection. They really break down when you want to use ML-based algorithms.
- sklogic 11y agoAnd why then Tesla is successful? A pure GPGPU, no use for gaming whatsoever.
- makomk 11y agoNvidia Tesla is still based around the same GPU architecture as NVidia's gaming GPUs, and in most cases even the exact same GPU chips. It benefits hugely from the R&D and economies of scale that come from it being based on a gaming product.
- qznc 11y agoAI? https://gigaom.com/2015/02/23/microsoft-is-building-fast-low-power-neural-networks-with-fpgas/ https://gigaom.com/2015/02/23/microsoft-is-building-fast-low... More precisely, to put AI on smart phones. Neural network is cheaper on FPGA. You can switch between AIs (voice/image/text recognition, games, etc) quickly and update them over the internet.