LAGER is an integrated computer-aided design (CAD) system for algorithm-specific h c g r a c d circuit(1C) design, targeted at applications such as speech processing, image processing, telecommunications, and robot control. LAGER provides user interfaces at behavioral, structural, and physical levels and allows easy integration of new CAD tools. LAGER consists of a behavioral mapper and a silicon assembler. The behavioral mapper maps the behavior onto a parameterized structure to produce microcode and parameter values. The silicon assembler then translates the filled-out structural description into a physical layout and with the aid of simulation tools, the user can fine tune the data path by iterating this process. The silicon assembler can also be used without the behavioral mapper for high sample rate applications. A number of algorithm-specific IC's designed with LAGER have been fabricated and tested, and as examples, a robot arm controller chip and a real-time image segmentation chip will be described.
We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.