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Re:Mill Computing in 2017 by the_duke on Thursday January 12, 2017 @08:41AM (#13382084)
Is it reasonably to still not be running on an FPGA after like 12+ years of working on it?
Re:Mill Computing in 2017 by pjc50 on Thursday January 12, 2017 @08:55AM (#13382173)
It seems that they're working on it somewhat part-time, and have prioritised getting the patents first. Which makes some sense as it's their only way to avoid being instantly destroyed by Intel.
Re:Mill Computing in 2017 by igodard on Thursday January 12, 2017 @02:27PM (#13385275)
Evolutionary development you can start at once, because you are building on what you had before; think an x86 generation. Evolution works if you already dominate a market and only need to run a little faster than your competitor. Evolution can be scheduled; tick-tock.

A newcomer can't sell yet another me-too, even with evolutionary improvement. Instead the newcomer has to rethink and create from first principles if it is to have any chance in the market. Rethinks can't be scheduled; they take as long as they take. Ours has taken longer than I'd hoped, but adding resources like more people to the project would have just slowed us down, or forced us to market with a broken product.

The Mill rethink stage is over, and we now can have reasonable schedules and put in more resources; that's why we are going out for a significant funding round this year, our first over $10M.

Re:Mill Computing in 2017 by nickpsecurity on Thursday January 12, 2017 @06:08PM (#13386999)
That doesn't sound right even though I support your niche strategy. Many of the successful companies had me too priducts with incremental, ecosystem, or marketing improvements. Intel did with x86 starting as an incremental improvement. AMD turned into huge company doing it to x86. Transmeta and Centaur did well adding power efficiency among other things. Quite a few vendors implemented POWER variants with many acquired or still doing good business.

There's plenty of it on software side, too, with the proprietary DOS's and UNIX's. Foreign cloners stayed doing it with mainframes and embedded CPU's. So, incremental stuff (esp patented) can certainly grab market share and generate revenue. It's been going on for some time even in CPU market even with dominant players.

Re:Mill Computing in 2017 by igodard on Thursday January 12, 2017 @06:41PM (#13387180)
Yes - by those with established businesses. I can't think of a startup that succeeded with an initial incremental, at lease since Amdahl. It's also hard to do an increment: the Intel teams are not dumb, and many could and have built far better processors than Intel has - but not while keeping compatibility and Intel's ROI and marketing and pricing structure. TransMeta tried - RIP.

There's also personal strategy involved. If we had done a better X86 we would have needed huge dollops of money to crack the front door of the market - c.f. TransMeta - and lost ownership of the company. By going for the disruptive approach we still own all of it - and funding rounds now are at a valuation that will keep us making our own mistakes, not someone else's. That matters to me, enough to go without paycheck for a decade. YMMV.

Re:Mill Computing in 2017 by pjc50 on Friday January 13, 2017 @08:41AM (#13390657)
Aren't almost all the businesses mentioned here extinct, or at least have tiny chunks of the market?
Re:Mill Computing in 2017 by nickpsecurity on Friday January 13, 2017 @10:05AM (#13391301)
More disruptive startups are. These were either running profitably or absolutely huge at one point. Blame AMD's and VIA's management for the rest on their end. ;)
Re:Mill Computing in 2017 by cma on Thursday January 12, 2017 @09:12PM (#13387890)
Starting out in x86, AMD had a license from Intel.
Re:Mill Computing in 2017 by nickpsecurity on Thursday January 12, 2017 @09:24PM (#13387938)
That justifies my use of it even more. Even with the license requirement, they still succeeded quite a bit. Even led on the 64-bit part since Intel screwed that up.
Re:Mill Computing in 2017 by willvarfar on Thursday January 12, 2017 @09:07AM (#13382237)
(Mill team)

Too right! 2017 is the year we get funding to go full-time and implement what we've been plotting at our Tuesday evening meetings for 10 years :)

Re:Mill Computing in 2017 by DennisP on Thursday January 12, 2017 @11:14AM (#13383393)
Hmm, if you had a model with 128-bit words that skipped floating point, and left out the sneaky stuff that makes some people distrust Intel and AMD processors, you'd have an almost ideal chip for Ethereum nodes. (Make it 256-bit words and it'd really be ideal.)

Not that that's a huge market at this point, but apparently there's a lot of Fortune 500 interest so maybe that'll change by the time you're in production.

Re:Mill Computing in 2017 by rogerbinns on Thursday January 12, 2017 @11:40AM (#13383669)
Something I don't see mentioned on your site is the rest of the hardware. Specifically is Mill intended to more of a co-processor with computing work handed over to it, or is it standalone in a system. If standalone what is the situation over bootup (eg UEFI or equivalent) and controllers like PCIe, USB, storage (NVME, SATA etc), NICs etc.
Re:Mill Computing in 2017 by baobrien on Thursday January 12, 2017 @01:24PM (#13384717)
AFAIK, It's intended as a general purpose processor.
Re:Mill Computing in 2017 by ChuckMcM on Thursday January 12, 2017 @08:56PM (#13387824)
And when you show a reference design for a smart phone with provably strong security capabilities its going to get very real indeed. Kudos for continuing the push toward real parts.
Re:Mill Computing in 2017 by pkaye on Thursday January 12, 2017 @10:37AM (#13383009)
But if you wait long enough your earlier ideas can no longer be patented due to prior art.
Re:Mill Computing in 2017 by phkahler on Thursday January 12, 2017 @09:38AM (#13382485)
If they run it on an FPGA the game will be over. The first questions to ask are how it compares in terms of performance and gate count to other architectures running some benchmarks. In particular they need to compare it to RISC V which is deliberately not patent encumbered and seems to be killing it in performance per area and per watt.

I can't say for certain that they'll fail. Maybe they'd be twice as good, but anything short of that and I just don't see viability.

Re:Mill Computing in 2017 by igodard on Thursday January 12, 2017 @02:35PM (#13385347)
Perhaps you are thinking that the FPGA is a product? It's not; it's an RTL validator. Moving chip RTL from FPGA to product silicon is a well understood step that is almost routine in the industry. Time was you would do initial RTL development work in silicon, but modern FPGAs are big enough to hold a whole CPU core. Today you wouldn't develop directly on the silicon without an FPGA step, even if you own a fab; it's just too expensive to debug.
Re:Mill Computing in 2017 by phkahler on Thursday January 12, 2017 @08:13PM (#13387653)
An FPGA will require an actual gate count, and it can give you a meaningful DMIPS/MHz number. Both of which are relevant metrics.
Re:Mill Computing in 2017 by jacobolus on Thursday January 12, 2017 @09:45AM (#13382544)
Their claim was ~10x improvement in performance / power compared to existing general-purpose CPUs.

> If they run it on an FPGA the game will be over.

Huh?

Re:Mill Computing in 2017 by phkahler on Thursday January 12, 2017 @09:53AM (#13382620)
That's great then. An FPGA implementation should be able to validate that. Even a fraction of that 10x improvement could change the world. So why does it take so long to benchmark an actual implementation? That's a rhetorical question, people implement CPUs in FPGAs all the time and this one is supposed to be simpler. There really is no excuse for it to take so long. They need to stop talking about their project and actually show us something.
Re:Mill Computing in 2017 by renox on Thursday January 12, 2017 @10:37AM (#13383007)
> That's a rhetorical question, people implement CPUs in FPGAs all the time and this one is supposed to be simpler.

Huh? You're not serious.. The Mill is definitively not simpler than many other CPUs (in order CPUs for example), what it is supposed to have is better performance or more exactly better performance/power ratio.

Re:Mill Computing in 2017 by protomikron on Thursday January 12, 2017 @01:07PM (#13384558)
I am not sure. I heard about the Mill some years ago and watched some presentations about the belt and my feeling was that it would be simpler to map functional languages onto it.

Maybe that was more wishful interpretation, but if I remember correctly the idea is to put more logic into the compiler (good old "sufficiently smart compiler") to do the optimization than do it at runtime in HW. IMHO this implies less logic in the HW which might make the implementation simpler (I am SW guy so my computer architecture knowledge might we skewed).

Further more I believe that we might be able to infer more and more bounds about runtime behavior that could possibly give rise to more aggressive optimizations. In particular the Mill provides more predictable performance than traditional architectures which is a feature in itself as it e.g. simplifies (again IMHO) real-time programming.

So that's why I believe the implementation hasn't to be at least harder than traditional architectures.

I am really looking forward to see some results and admire their effort.

Re:Mill Computing in 2017 by __s on Thursday January 12, 2017 @05:33PM (#13386792)
The belt's designed to be easily compiled to (register coloring is NP hard) but it requires the CPU analyse data flow somewhat to optimize in a way where there isn't a bunch of data copying. Godard frequently explains that the belt is conceptual, that the hardware should be doing optimizations underneath

Whereas for a simple architecture registers are simple: they index into the register file. This only breaks down when we bring in out-of-order & register renaming in order to have more registers than the instruction set specifies

Re:Mill Computing in 2017 by igodard on Thursday January 12, 2017 @06:48PM (#13387231)
Optimal register coloring is NP hard, but no compiler does that; heuristics are no worse than quadratic and give near-optimal.

The Mill specializer part that schedules ops is linear, while the part that assigns belt numbers and inserts spills is NlogN in the number of ops in an EBB because it does some sorts.

Re:Mill Computing in 2017 by petecox on Thursday January 12, 2017 @07:00PM (#13387298)
> my feeling was that it would be simpler to map functional languages onto it

I found this [1] blog post interesting - that mainstream architectures have defaulted to low level C-machines and that radically new CPU designs might return to the halcyon days of lisp.

[1]http://liam-on-linux.livejournal.com/43040.html

Re:Mill Computing in 2017 by protomikron on Saturday January 14, 2017 @10:57AM (#13398934)
Thx, that was an interesting read.

However I think that Lisp is too powerful to be executed directly on the machine (as I understand Lisp machines provide HW capabilities to deal with cons and list atoms).

I often wonder if we should try to make a non Turing complete language, but that we make "pseudo-turing-complete", by using some kind of bounded-automaton with insane worst-case upper bounds (e.g. about complexity) that we can feed to the OS/machine which then can aggressively schedule as it knows upper timing bounds etc.

Btw. is their good literature about the implementation of intermediate languages as compilation targets for static functional languages? I think the book to go was SPJ's "The Implementation of Functional Programming Languages", but I am not sure how relevant it is today.

Re:Mill Computing in 2017 by kazinator on Sunday January 15, 2017 @05:01AM (#13403309)
To "execute Lisp directly" means to interpret the AST. No hardware machine does that that I know of. It can almost certainly be done, but arguably shouldn't. Interpreting the raw syntax is a bootstrapping technique to which it would seem foolish to commit a full-blown hardware implementation.
Re:Mill Computing in 2017 by lispm on Sunday January 15, 2017 @12:23PM (#13405038)
Re:Mill Computing in 2017 by renox on Thursday January 12, 2017 @06:42PM (#13387196)
The Mill is simpler that many CPU because it isn't OoO and it has a single address space but it also has some magic in it (the way it zeros memory, the stacks..) which aren't free to implement.
Re:Mill Computing in 2017 by LeifCarrotson on Thursday January 12, 2017 @10:44AM (#13383076)
An FPGA implementation on general-purpose fabric will not validate the performance/watt when compared to dedicated silicon. The two aren't comparable. This is part of the reason modern FPGAs have onboard ARM processors, as well as graphics and I/O peripherals.
Re:Mill Computing in 2017 by phkahler on Thursday January 12, 2017 @03:20PM (#13385740)
>> An FPGA implementation on general-purpose fabric will not validate the performance/watt when compared to dedicated silicon.

No of course not. But it will validate benchmarks per-clock cycle, as well as providing a gate count (or LUT count) required to achieve that benchmark result. If the architecture is anywhere near as awesome as claimed, there should be a strong indication of that in the numbers produced by the FPGA implementation.