The article makes the point that your technique will give an advantage to academic teams that don't have the resourcers of big corporations. To me it seems that your technique optimises the use of available resources, but the amount of available resources remains the deciding advantage. That is to say, both large corporate teams and smaller academic teams can improve their use of resources using your proposed approach, but large corporate teams have more of those than the smaller academic teams. So the large corporate teams will still come up ahead and the smaller academic teams will still be left "in the dust" as the article puts it. What do you think?
The key is that large corporations/labs achieve scale through many distributed machines. This paper explores optimizations that are particular to a single multi-core machine. These optimizations exploit low-latency shared memory between threads on one machine, and thus cannot be replicated on a distributed cluster.
The article makes the point that your technique will give an advantage to academic teams that don't have the resourcers of big corporations. To me it seems that your technique optimises the use of available resources, but the amount of available resources remains the deciding advantage. That is to say, both large corporate teams and smaller academic teams can improve their use of resources using your proposed approach, but large corporate teams have more of those than the smaller academic teams. So the large corporate teams will still come up ahead and the smaller academic teams will still be left "in the dust" as the article puts it. What do you think?