Fujitsu's 'DLU' AI Processor Promises 10x The Performance Of 'The Competition'

[Guest]

In addition to the company's plans to build an AI supercomputer with 24 Nvidia DGX-1 systems, Fujitsu also plans to produce an AI processor delivering more than ten times the performance per watt than the competition by 2018.

Fujitsu's 'DLU' AI Processor Promises 10x The Performance Of 'The Competition' : Read more

 

[tslot05qsljgo9ed]

Quote: 10x Performance / Watt compared to competitors

Are they comparing that number 10x to past products (Nvidia Pascal) or current products (Nvidia Volta).

Nvidia is not standing still and they too will have new products in 2018.

 

[FranticPonE]

It's a GPU's general purpose SIMD units... that's more efficient because they say it will be. "Look our 'master units' coordinate memory access and SIMD units!" ... Exactly like GPU "wavefronts" or whatever do now. Good job Fujitsu, you reinvented the wheel then bragged about it. Just like Google did with their own "Deep Learning" chip, and just like Google's chip it will no doubt be no faster nor more efficient than what Nvidia and AMD already do.

 

[bit_user]

... with a scalable design utilizing the company's Tofu interconnect technology

I love it! Finally, something Japanese-sounding in a Japanese chip!

Seriously, did Fujitsu ever set any records with their SPARC CPUs? I don't recall reading anything about it, but I don't follow the supercomputer or mainframe sectors very closely.

I was hoping to see some exotic new technology, like phase-change memory embedded with the processing elements. But, unless their Tofu interconnect somehow lets them scale incredibly well, I just don't see any reason they should beat (or even match) Volta or Google's Gen2 TPU.

 

[bit_user]

It's a GPU's general purpose SIMD units... that's more efficient because they say it will be.

Yes. The whole thing seems incredibly GPU-like, to me. I guess it has the advantage that latencies and memory access patterns could be more predictable, allowing for a number of simplifications not possible in GPUs. But you don't get an order of magnitude from that.

Good luck to them.

 

[Xajel]

I don't know why when I was reading the comments I remembered Matrox Parhelia-512 ??