<story><title>David Patterson Says It’s Time for New Computer Architectures and Languages</title><url>https://spectrum.ieee.org/view-from-the-valley/computing/hardware/david-patterson-says-its-time-for-new-computer-architectures-and-software-languages</url></story><parent_chain><item><author>Animats</author><text>It&amp;#x27;s really hard. Remember the Itanium and the Cell. You can build it, but they may not come.&lt;p&gt;GPUs, though. Those have turned out to be very successful, they can be parallelized as much as you&amp;#x27;re willing to pay for, and they&amp;#x27;re good for some non-graphics tasks.&lt;p&gt;Much of machine learning is a simple repetitive computation running at low precision. Special purpose hardware can do that very well.&lt;p&gt;So what&amp;#x27;s the next useful thing in that area?</text></item></parent_chain><comment><author>snaky</author><text>&amp;gt; Remember the Itanium&lt;p&gt;Well, why not.&lt;p&gt;&amp;gt; Q: I feel like deja vu - at Hot Chips, Intel introduced VLIW-concept Itanium that pushed complexity onto the compiler. I see traces of that here. What are you doing to avoid the Itanium traps? How will you avoid IP from Intel?&lt;p&gt;&amp;gt; A: Itanium was in-order VLIW, hope people will build compiler to get perf. We came from opposite direction - we use dynamic scheduling. We are not VLIW, every node defines sub-graphs and dependent instructions. We designed the compiler first. We build hardware around the compiler, Intel approach the opposite.&lt;p&gt;&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.anandtech.com&amp;#x2F;show&amp;#x2F;13255&amp;#x2F;hot-chips-2018-tachyum-prodigy-cpu-live-blog&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.anandtech.com&amp;#x2F;show&amp;#x2F;13255&amp;#x2F;hot-chips-2018-tachyum-...&lt;/a&gt;</text></comment>
<story><title>David Patterson Says It’s Time for New Computer Architectures and Languages</title><url>https://spectrum.ieee.org/view-from-the-valley/computing/hardware/david-patterson-says-its-time-for-new-computer-architectures-and-software-languages</url></story><parent_chain><item><author>Animats</author><text>It&amp;#x27;s really hard. Remember the Itanium and the Cell. You can build it, but they may not come.&lt;p&gt;GPUs, though. Those have turned out to be very successful, they can be parallelized as much as you&amp;#x27;re willing to pay for, and they&amp;#x27;re good for some non-graphics tasks.&lt;p&gt;Much of machine learning is a simple repetitive computation running at low precision. Special purpose hardware can do that very well.&lt;p&gt;So what&amp;#x27;s the next useful thing in that area?</text></item></parent_chain><comment><author>marcosdumay</author><text>Well, past experiences are not that useful right now. I don&amp;#x27;t think the Itanium or the Cell were great architectures, but it&amp;#x27;s clear that their most obvious failure mode (mainstream architectures improving faster than them) isn&amp;#x27;t a showstopper anymore.&lt;p&gt;For some guess on the next big thing, I would imagine that stuff that avoid the need of memory coherence have nice odds.</text></comment>