Congress recently passed the Department of Energy Research and Innovation Act (H.R.589) which essentially authorizes many existing Department of Energy activities. It also emphasizes efforts to ease and accelerate technology transfer to the private sector. The bill was first introduced back in January of 2017, quickly passed by the House but not passed by the Senate until this July, and just signed by President Trump on September 28, 2018. It has three main elements:
- Laboratory and Technology Transfer
- Department of Energy Research Coordination
- Department of Energy Office Science Policy
A key provision of the Technology Transfer portion of the bill provides authority to “the directors of the National Laboratories to use funds authorized to support technology transfer within the Department to carry out early stage and precommercial technology demonstration activities to remove technology barriers that limit private sector interest and demonstrate potential commercial applications of any research and technologies arising from National Laboratory activities.”
DOE’s Cost-Share Pilot program also received tweaks. The bill mandated a report “as soon as practicable” on the use of cost waivers during the past two years and annual reports going forward for the two years remaining on the cost-sharing program. In fact, several assessment reports connected with various programs were mandated.
According to one observer there is little really new in the legislation and that it largely covers things the DOE is already doing such as ARPA-E, exascale computing, and the BRAIN initiative. There is a section (sec. 304) related to Advanced Scientific Computing Research (ASCR) that likewise covers mostly familiar ground. It reiterates the mandate to “development of two or more exascale computing machine architectures, to promote the missions of the Department” and “development of “two or more exascale computing architectures”.
For the moment, exascale means just that according to the bill – “computing through the use of a computing machine that performs near or above 10 to the 18th power operations per second.” This varies from the Exascale Computing Project’s characterization of “delivery of a capable exascale computing ecosystem that delivers 50 times more computational science and data analytic application power than possible with DOE HPC systems such as Titan (ORNL) and Sequoia (LLNL).” The hope, of course, is to attain both.
It’s best to scan the bill for areas of particular interest.