The model can vary task allocation between cores, neural networks and accelerators size the system parameters create an equilibrium between response time and power consumption and select the scheduler and buffer strategy. The AI Designer enables an architect to rapidly construct a graphical model using parameterized IP and integrating around an interconnect such as a Network-on-Chip, Quantum Nodes or in-Memory elements.The user can accurately simulate AI workloads and real-life interface traffic. “The complex model requires configurable IPs and an integrated simulation environment.” “The best processor configuration depends on the application, price point and the expected performance.Trying to predict the feasibility before building the first prototype requires modelling IP, which is never readily available.The intense competition in the marketplace makes the delay in detecting performance limitation, a major detriment to a successful new product introduction”, said Deepak Shankar, Vice President – Technology, Mirabilis Design. At the system-level, VisualSim AI can be integrated with a network model and FPGA boards for full system verification. The IP available in the VisualSim AI brings together processor cores, neural networks, accelerators, GPU and DSP. It can be used for the architecture evaluation of AI processor hardware, partition AI algorithms on a System-on-Chip (SoC), test the AI/ML implementation, and measure power and performance of an AI processor across a number of applications. VisualSim AI is able to accelerate time-to-market of new AI technology, configures high-performance computing systems, eliminates under and over-design, and provides an interactive reference design for end-users to create new applications. Mirabilis Design, a provider of system-level IP and Simulation Solutions for electronics and processors, has released the VisualSim AI Processor Designer.

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