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.
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. The IP available in the VisualSim AI brings together processor cores, neural networks, accelerators, GPU and DSP. At the system-level, VisualSim AI can be integrated with a network model and FPGA boards for full system verification.
“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. “The complex model requires configurable IPs and an integrated simulation environment.”
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 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 combination of the large model capacity, fast model construction, an extremely fast simulator, and a programmable analytics engine, enables users to rapidly arrive at the most suitable architecture.
Users can run software on the VisualSim AI architecture to measure response times, power, network throughput, cache hit-ratio, and memory bandwidth.
VisualSim AI will enable users to optimise and validate the SoC system specification, and system companies to select the right SoC for the target application.
A number of beta customers have utilised this platform to design AI SoC for the data centre and automotive applications.
Other applications that can use this platform are autonomous driving, radars’ processing, defence systems, flight avionics, medical instruments, high performance computing and infotainment systems.
