George Michelogiannakis, Dave Donofrio, John Shalf, "Modeling of Novel Transistors, Manufacturing Technologies, and Architectures to Preserve Digital Computing Performance Scaling", 1ST INTERNATIONAL WORKSHOP ON POST-MOORE’S ERA SUPERCOMPUTING (PMES), November 2016,
- Download File: pmes.pdf (pdf: 103 KB)
Farzad Fatollahi-Fard, David Donofrio, George Michelogiannakis, John Shalf, "OpenSoC Fabric: On-Chip Network Generator", ISPASS 2016: International Symposium on Performance Analysis of Systems and Software, IEEE, April 2016,
Farzad Fatollahi-Fard, David Donofrio, George Michelogiannakis, John Shalf, "OpenSoC Fabric: On-Chip Network Generator", Proceedings of the Workshop on Network on Chip Architectures, ACM, December 2014, 45-50, LBNL LBNL-1005675, doi: 10.1145/2685342.2685351
- Download File: opensocnocarc.pdf (pdf: 1.1 MB)
John Shalf, Donofrio, Rowen, Oliker, Michael F. Wehner, "Green Flash: Climate Machine (LBNL)", Encyclopedia of Parallel Computing, (Springer: 2010) Pages: 809-819
Green Flash is a research project focused on an application-driven manycore chip design that leverages commodity-embedded circuit designs and hardware/software codesign processes to create a highly programmable and energy-efficient HPC design. The project demonstrates how a multidisciplinary hardware/software codesign process that facilitates close interactions between applications scientists, computer scientists, and hardware engineers can be used to develop a system tailored for the requirements of scientific computing.
George Michelogiannakis, David Donofrio, John Shalf, Modeling of Novel Transistors, Manufacturing Technologies, and Architectures to Preserve Digital Computing Performance Scaling, Post-Moore's Era Supercomputing (PMES) Workshop, November 2016,
- Download File: PMES-2016.pptx (pptx: 4.5 MB)
George Michelogiannakis, John Shalf, David Donofrio, John Bachan,, "Continuing the Scaling of Digital Computing Post Moore’s Law", LBNL report, April 2016, LBNL 1005126,
The approaching end of traditional CMOS technology scaling that up until now followed Moore's law is coming to an end in the next decade. However, the DOE has come to depend on the rapid, predictable, and cheap scaling of computing performance to meet mission needs for scientific theory, large scale experiments, and national security. Moving forward, performance scaling of digital computing will need to originate from energy and cost reductions that are a result of novel architectures, devices, manufacturing technologies, and programming models. The deeper issue presented by these changes is the threat to DOE’s mission and to the future economic growth of the U.S. computing industry and to society as a whole. With the impending end of Moore’s law, it is imperative for the Office of Advanced Scientific Computing Research (ASCR) to develop a balanced research agenda to assess the viability of novel semiconductor technologies and navigate the ensuing challenges. This report identifies four areas and research directions for ASCR and how each can be used to preserve performance scaling of digital computing beyond exascale and after Moore's law ends.