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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.

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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.

The trace-back technique is an effective approach for survivor memory management in the Viterbi algorithm. It is especially attractive when the number of states in the trellis is large, in which case the register exchange approach is impractical due to the area required for wiring. Previous descriptions of the trace-back technique have assumed either one or two trace-back pointers and have made specific assumptions about the speeds of those pointers. In this paper we present a general framework for implementing the trace-back technique with any number of traceback pointers and with relaxed assumptions about the speeds of the pointers. We also show that the use of additional trace-back pointers reduces the memory requirements. Two implementations of the generalized trace-back techniques based on standard RAMs and custom shift registers are presented.

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Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.