To drive architecture and system-level studies into 3D ReRAM and other emerging memory technologies, a group of researchers at Oak Ridge National Lab, Penn State and UCSB have developed a modeling tool named DESTINY. DESTINY is an acronym for 3D dEsign-Space exploraTIon tool for SRAM, eDRAM and Non-volatile memorY. It can model both 2D and 3D caches designed with five prominent memory technologies: ReRAM, STT-RAM, PCM, eDRAM and SRAM, at technology nodes ranging from 22nm to 180nm. Thus, DESTINY is a comprehensive tool which can model both conventional and emerging technologies.
DESTINY facilitates design-space exploration across several dimensions, such as optimizing for a target (e.g. latency or area) for a given memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a desired optimization target etc. DESTINY has been validated against several industrial cache prototypes.
This table compares the features of DESTINY with other existing modeling tools.
The DESTINY code can be downloaded from code.ornl.gov/3d_cache_modeling_tool/destiny
DESTINY should be compiled with a user-specified configuration file ($ ./destiny *.cfg). The output of DESTINY is the area, latency and energy values for the cache. More details can be found in the manual entitled ”DESTINY_Documentation” in folder ‘Doc’ in the git repository. This file shows an example configuration file and the corresponding output of DESTINY, which may be especially useful for a user who wants to get an overview of DESTINY even before installing it.
The following DATE-2015 paper provides a general introduction of DESTINY: Matt Poremba, Sparsh Mittal, Dong Li, Jeffrey S Vetter and Yuan Xie, “DESTINY: A Tool for Modeling Emerging 3D NVM and eDRAM caches”, DATE, 2015.
Sparsh Mittal received the B.Tech. degree from IIT, Roorkee, India and the Ph.D. degree in computer engineering from Iowa State University. He is currently working as a Post-Doctoral Research Associate at ORNL. His contact email address is sparsh0mittal at gmail.com
Matt Poremba received a Ph.D. degree in Computer Science and Engineering from the Pennsylvania State University. He is currently working as a Post-Doctoral Researcher at AMD Research.
Jeffrey S. Vetter received the PhD degree from Georgia Institute of Technology. He is currently working as a Distinguished R&D Staff Member, and the founding group leader of the Future Technologies Group at ORNL.
Yuan Xie received the PhD degree from Princeton University. He is currently working as a Professor at University of California at Santa Barbara.