The excitement comes from the fact that some workloads benefit greatly from GPUs -- mostly those where the GPU arch offers some niche-advantage that can give GP

The excitement comes from the fact that some workloads benefit greatly from GPUs -- mostly those where the GPU arch offers some niche-advantage that can give GPUs >=10x perf[/W]. A good example is deep learning where Intel is struggling to compete [1], and even in linear algebra there is a 4-5x power efficiency difference [2, slide 6]. At the same time, in many other complex applications the performance/W/$ advantage has not been all that clear, especially since GPUs have been quite behind in process technology. A good example is a simulation code I work on where a 2-4x speedup from GPUs, which (due to inherent overhead of using accelerators) gradually vanishes in strong scaling, means that when price is considered, only cheap consumer cards can imrpove the performance/buck metric significantly (that's time-to-solution/buck in our case), professional cards don't offer significant significant improvements other than performance density [3, figures 6,7]. There are plenty more examples that NVIDIA collects [4], but always take the claims with a grain of salt, especially the ones with "incredible" >10x speedup claims :) Last, I'd note that with the recent 14-16nm jump, the gap between the traditional CPUs and the simpler accelerator architectures has increased (I've just seen MAGMA BLAS on Tesla P100 results which show >10x GFlops/W, more than double that of the previous arch) and I expect it to keep increasing partly due to the manufacturing/process technology gap shrinking between Intel and the rest and partly due to architecture and programmability improvements of accelerators. [1] https://www.nvidia.com/object/gpu-accelerated-applications-tensorflow-benchmarks.html https://www.nvidia.com/object/gpu-accelerated-applications-t... [2] http://on-demand.gputechconf.com/gtc/2015/presentation/S5476-Stanimire-Tomov.pdf http://on-demand.gputechconf.com/gtc/2015/presentation/S5476... [3] https://www.academia.edu/13753737/Best_bang_for_your_buck_GPU_nodes_for_GROMACS_biomolecular_simulations https://www.academia.edu/13753737/Best_bang_for_your_buck_GP... [4] https://www.nvidia.com/object/gpu-applications.html https://www.nvidia.com/object/gpu-applications.html