Can Photonic Computing be the Answer to Green and Sustainable Computing For decades now, processing speed has been consistently rising. The top supercomputer, Summit, today, can perform 148,600 trillion calculations in one second (148.6 PF on LINPAC). Exascale supercomputers that can perform more than one million trillion (quintillion) calculations per second are planned for 2021. However, this smooth ride is almost over with the end of Moorexe2x80x99s Law and Dennardxe2x80x99s Scaling due to the increased power consumption and leakage. Scientists believe that we are reaching serious physical limits. Innovative ideas in device technology and architectures are a must for the next generation of computing. Photonic devices are characterized by their speed and ultralow power. In this talk we examine the use of alternative Photonic computing architectures based on these devices, on the chip, to solve many critical science and engineering problems, including Partial Differential Equations (the basis for scientific and engineering simulations) and machine learning. We use this to examine the potential and progress needed to reap the full benefits of this technology and move it to becoming a main stream fast green computing alternative.

A New Traffic Offloading Method with Slow Switching Optical Device in Exascale Computer The expected exascale computer will comprise tens of thousands of computing nodes and nearly 5000 interconnected nodes in years to come. Such a largescale system will represent a milestone in the progress of HighPerformance Computing (HPC). The more efficient network hardware, like optoelectronic interconnection and configurable switches, is reforming the traditional architecture of supercomputers. However, the present architecture containing new hardware is not easy to adapt to the dynamically running condition, because the newly developed hardware is normally unable to effectively improve overall performance. Here, we propose a new accelerated system called Software Defined Network Accelerator (sDNA) for the exascale computer. Inspired by edge forwarding index (EFI), the main contribution of our work is that it presents an extended EFIbased optical interconnection method with slow switching optical device. The optical link is connected by the evaluation of each optical link candidateu0027s traffic offloading revenue. As the supporting method for optical interconnection, sDNA selects the most suitable routing configuration according to the jobschedule information and the priorknowledge of HPC applications. We tested sDNA in a network simulator and a prototype system for the exascale computer, using both DOE application benchmarks and a realworld communication benchmark. From the result of verification of traffic offloading, we found that our optical interconnection method based on our extended EFI evaluation is not only able to offload the traffic from an electrical link to an optical link but is also able to avoid congestion inherent to electrical link. Furthermore, our experimental results show that sDNA maintains the throughput of more than 80% bandwidth and reduced the communication delay by 10% in our real prototype system and simulator. Together, our sDNA is an ideal candidate for accelerating communication performance of the exascale computer.