Promises, Challenges Ahead for Near-Memory, In-Memory Processing
The idea of bringing compute and memory functions in computers closer together physically within the systems to accelerate the processing of data is not a new one. …
The idea of bringing compute and memory functions in computers closer together physically within the systems to accelerate the processing of data is not a new one. …
What supercomputers will look like in the future, post-Moore’s Law, is still a bit hazy. …
It has just been announced that there has been a shift in thinking among the exascale computing leads in the U.S. …
Clustering together commodity servers has allowed the economies of scale that enable large-scale cloud computing, but as we look to the future of big infrastructure beyond Moore’s Law, how might bleeding edge technologies capture similar share and mass production? …
If there is any organization on the planet that has had a closer view of the coming demise of Moore’s Law, it is the Institute of Electrical and Electronics Engineers (IEEE). …
Although the timeline for reaching exascale class computing continues to stretch farther into the future, research teams are keeping an eye on what technologies will shape the machines of the post-exascale timeframe, which is in the 2022-2030 timeframe. …
We have heard about a great number of new architectures and approaches to scalable and efficient deep learning processing that sit outside of the standard CPU, GPU, and FPGA box and while each is different, many are leveraging a common element at all-important memory layer. …
Over the long course of IT history, the burden has been on the software side to keep pace with rapid hardware advances—to exploit new capabilities and boldly go where no benchmarks have gone before. …
In the last couple of years, we have examined how deep learning shops are thinking about hardware. …
The supercomputing industry is as insatiable as it is dreamy. We have not even reached our ambitions of hitting the exascale level of performance in a single system by the end of this decade, and we are stretching our vision out to the far future and wondering how the capacity of our largest machines will scale by many orders of magnitude more. …
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