This is a fascinating development. We’re going to need real innovation in hardware (software, too), especially as Moore’s Law starts to run out of steam.
Computer scientists from Rice University, along with collaborators from Intel, have developed a more cost-efficient alternative to GPU.
The new algorithm is called “sub-linear deep learning engine” (SLIDE), and it uses general-purpose central processing units (CPUs) without specialized acceleration hardware.
One of the biggest challenges within artificial intelligence (AI) surrounds specialized acceleration hardware such as graphics processing units (GPUs). Before the new developments, it was believed that in order to speed up deep learning technology, the use of this specialized acceleration hardware was required.