The Federal Reserve Bank of Kansas City’s (KC Fed) Center for the Advancement of Data and Research in Economics (CADRE) is soliciting presentations and participation in the third Economic Research in High Performance Computing (HPC) Environments workshop on October 11-12, 2017. The theme this year is “HPC and Advancing the Economic Research Agenda.” Please see below for additional information on the presentations they are seeking.
Attached to this blog post is a flyer to pass around to anyone who may be interested: FRBKC_CfP_HPC_2017
Attendance is free but registration is required and space is limited. If you are interested in presenting or have faculty that would be interested in presenting, please send an email to email@example.com. Please share this information with interested colleagues.
Registration and information on travel and lodging will be available later in the summer.
The theme of this year’s workshop is “HPC and Advancing the Economic Research Agenda.” As we continue with CADRE’s mission of supporting, enhancing, and advancing data or computationally intensive economic research, we are looking to provide examples of and guidance for how high performance computing can shape the economic research landscape.
To that end, the KC Fed seek two types of presentations:
- Economic research that was fundamentally enabled or vastly improved by the use of HPC techniques and technologies. The presentations should highlight the role of the proper utilization of HPC and emphasize the costs and benefits of that utilization over alternative techniques and technologies.
- Technology and methodological applications that might help shape the economic research landscape in the future. As new technologies and techniques become more visible in the statistics, computer science, and technology realms, how might we think about applications for economic and financial research? Some examples might be, but are not limited to:
- Using R with Big Data
- Natural language processing and understanding
- Large-scale neural networks and deep learning
- Agent-based modeling with GPUs
- Automated machine learning at scale
- Containerization for sharing and reproducibility
The KC Fed is especially interested in presentations that can connect new or emerging applications to estimation or simulation approaches similar to those done in the economic or financial literature.