Comment by nkurz | Hacker News Reader

Comment by nkurz | Hacker News Reader

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In terms of raw compute speed, it seems like the FX-9590 will be at least the same speed.

They aren't really comparable. An FX-9590 at 4.7GHz is about 300 GFlops, but the the Xeon Phi 31S1P is slightly over 1 TFlop --- more than 3x as many floating point operations per second. The spec that probably shows the most difference is memory bandwidth. The FX-9590 with 1866 memory achieves 30GB/s. The Phi reaches 320GB/s, about 10 times as much. The presumption is that you might put 4 of these in a server, in addition to the standard processors.

The price is actually quite a bit better, too, as some vendors are offering the Phi at $125 each in quantities of 10: http://www.colfax-intl.com/nd/xeonphi/31s1p-promo.aspx

This article offers some good information about cases where the Phi is a good (or bad) choice: https://software.intel.com/sites/default/files/article/33016...

The short answer would be that the Phi might be the best choice in cases where you need to perform billions of energy efficient floating point operations on a working set small enough to fit in the cards RAM, where the degree of branching is such that a "normal" GPU would be inappropriate, and where the problem justifies considerable programmer time for optimization. Financial and scientific models are the usual examples.

Ok, but if the normal price is 2000USD, then that leaves space for a lot of 9590s. You could get almost the same memory bandwidth and 3x as much processing power with 10 9590s. And remember that's floating point performance; the bulldozer architecture the 9590 is based on gives you about effectively 1.5x as many cores when doing integer operations.

So, ok, the Phi is useful at the current price, but at the 2000USD price other people are talking about in the thread it seems pretty useless.

You also need n number of motherboards, RAM, power supplies, etc as you have CPUs. The Phi looks a lot better when you fit 5-6 in a server.

Everyone in this thread keeps railing on its floating point perf, which is about on par with parts like nVidia's Tesla and similarly priced... but its integer performance is why people are really buying these cards up. All GPUs are floating point monsters but integer pansies because that's what their graphics workload heritage turned them into. Xeon Phi is a Computing Monster, with crazy Integer and Floating Point perf, because its heritage was "Let's try to make a graphics card out of CPUs" and not visa versa. It's similar to buying a whole stack of x86 chips just to get to the SSE/AVX units. Only, now you don't need a whole stack of computers, you need a handful of host computers and a stack of add-on cards.

And if you think $2000 is expensive for 60 x86 cores (~$35/core) when all you care about is the SSE/AVX unit and how many vector ops you can cram through it, you're definitely not Intel's target.

Thanks, you are right that I shouldn't have focussed on just floating point. I emphasized it because it better matched the frequently quoted "teraflop in a single card" measurement. As you say, the Phi is equally strong at vector integer operations as floating point, in both cases operating on 512-bit vectors.

But I'll quibble with the assertion that all GPU's are "integer pansies", although it's a fantastic phrase. Historically, NVidia GPU's are much stronger at floating point operations than integer because of their graphics origins, and NVidia's Tesla is definitely what Intel views as nearest to the Phi's target market.

But AMD/ATI cards have excellent vector integer performance, several times that of NVidia/Tesla, and much better per dollar than Phi until this recent price drop. This is why AMD cards were the best choice for bitcoin mining until the recent arrival of dedicated ASIC's: http://www.extremetech.com/computing/153467-amd-destroys-nvi...

As per another post above:

> It doesn't support CMOV, MMX, SSE, AVX, and all other ISA extensions the popped up after the original Pentium.

I'm not saying it's not useful, it's just not quite as useful as having 60 cores that can just run MMX/SSE/AVX.

> The short answer would be that the Phi might be the best choice in cases where you need to perform billions of energy efficient floating point operations on a working set small enough to fit in the cards RAM

I'm confused by this. You previously stated that memory bandwidth on the Phi is 10x as high as on the FX-9590. Based on this, I would say that the Phi would be better suited at jobs which require lots of data that doesn't fit in main memory.

I might be wrong, but I think his speeds are from the internal ram of the Phi and the FX-9590 to their processors, not the transfer speed from the hard drive to the cards ram. So if all of the data fits in the Phi's ram it can transfer that to the processors really fast, but if you have to transfer over the PCI you are limited to those speeds.

You are right. The largest Xeon Phi's have 16GB of GDDR5 memory on the card, and the 31S1P on sale has 8GB. The quoted speeds are for 16-channel transfer between the card's on board memory and the cores on the same card. Transfer from main memory back and forth to the card is over PCIe v2 x16 which has a theoretical max of 8 GB/s --- about 3% of the maximum transfer rate on data within the card.

So if your working data set fits on the card (less than 8/16 GB), or can be partitioned so that it fits on multiple cards, you can potentially get great performance from Phi. But if it's larger than this, especially if it is less than 1TB and would thus fit in the host's RAM, transfer from the host to the card will likely destroy any performance advantage.

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