--- title: Offload Multiple Signal Classification (MUSIto AMD Versal™ AI Engines | Fidus On - Demand Webinar description: Access the on-demand webinar showcasing how to accelerate MUSIC algorithms using AMD Versal AI Engines for high-performance DSP applications in radar, sonar, and wireless systems. --- [Skip to main content](https://info.fidus.com/offload-multiple-signal-classification-music-to-amd-versal-ai-engines#main) ![logo-white](https://info.fidus.com/hubfs/logo-white.svg) ![logo-white](https://info.fidus.com/hubfs/logo-white.svg) Open main navigation Close main navigation [![AMD-Premier\_ACP-Logo](https://info.fidus.com/hs-fs/hubfs/Partner%20Logos/AMD-Premier_ACP-Logo.png?width=302&height=77&name=AMD-Premier_ACP-Logo.png)](https://fidus.com/partners/amd/) # Offload Multiple Signal Classification (MUSIC) to AMD Versal™ AI Engines ### WEBINAR RECORDING ON-DEMAND **Presenters**: - [Bachir Berkane](https://www.linkedin.com/in/bachir-berkane-22708029/), System and Algorithm Architect at Fidus Systems - [Peifang Zhou](https://www.linkedin.com/in/peifang-zhou-5bba858/), Senior Embedded Software Designer at Fidus Systems - [Mark Rollins](https://www.linkedin.com/in/drmarkrollins/), Ph.D., Sr. Manager Technical Marketing at AMD **Duration:** 60 minutes *Missed the live webinar? No worries! You can now access the on-demand version of our insightful webinar.* ![AMDFidus On-demand Webinar Post 1200X628 px (LinkedIn Post) (1200 x 628 px) (2)](https://info.fidus.com/hs-fs/hubfs/AMDFidus%20On-demand%20Webinar%20Post%201200X628%20px%20(LinkedIn%20Post)%20(1200%20x%20628%20px)%20(2).png?width=1117&height=586&name=AMDFidus%20On-demand%20Webinar%20Post%201200X628%20px%20(LinkedIn%20Post)%20(1200%20x%20628%20px)%20(2).png) In[partnership with AMD](https://fidus.com/partners/amd/), join us for an in-depth presentation on how high-performance DSP algorithms can be accelerated using [AMD Versal](https://fidus.com/services/build-for-amd-versal-adaptive-socs-fpgas/)AI Engine technology. We showcase the implementation of a [MUSIC (Multiple Signal Classification) algorithm](https://docs.amd.com/r/en-US/Vitis-Tutorials-AI-Engine-Development/MUltiple-SIgnal-Classification-MUSIC-Algorithm-on-AI-Engine)—widely adopted in radar, sonar, and wireless systems—to demonstrate the advanced compute capabilities of Versal Adaptive SoCs. **MUSIC algorithms are deployed across applications requiring:** •    Direction of Arrival (DOA) estimation •    Frequency & Spectral Estimation •    Modal Analysis •    Blind Source Separation Due to their significant computational demands, MUSIC algorithms are ideal candidates for acceleration using Versal AI Engines. This project, developed in collaboration between [AMD](https://www.amd.com/en.html) and [Fidus Systems](https://fidus.com/services/fpga-design/), demonstrates how real-time performance was achieved using efficient C/C++ kernel development and pipelined AI Engine tile architectures. **Why watch the webinar?** - **End-to-End Implementation of the MUSIC Algorithm:** Gain a complete understanding of how Multiple Signal Classification (MUSIC) is structured and deployed—from signal modeling and QR decomposition to SVD-based subspace separation and spatial spectrum analysis for Direction of Arrival (DOA) estimation. - **Real-Time Performance Using AMD Versal AI Engines:** See how Fidus mapped MUSIC onto AMD’s Versal AI Engine array, achieving a 1 microsecond throughput using 150 tiles with fully pipelined, vectorized kernel implementations in C/C++. - **AI Engine Architecture Deep Dive:** Explore the 2D array of VLIW processors and memory tiles that power Versal’s AI Engine, including details on SIMD vector units, instruction-level parallelism (7-way VLIW), and deterministic interconnect strategies for high-performance DSP workloads. - **Loop Unrolling and Tile Mapping Strategy:** Understand how key algorithm components—QRD, SVD, spectrum computation, and DOA search—were transformed into deep pipeline stages using loop unrolling, efficient data movement, and local memory sharing between tiles. - **Hardware-in-the-Loop (HIL) Demonstration:** Watch a real-time demo that integrates MATLAB snapshot generation with MUSIC execution on the AMD VCK190 evaluation board. See how results—including DOA plots and spectrum profiles—are visualized and validated over TCP/IP. - **C/C++ Design Best Practices for AI Engine:** Learn how the Fidus team used compiler directives, data-level parallelism, and static memory optimization to maximize performance, plus lessons learned shared via published design blogs. - **Scalability and Future Use Cases:** Discover how this approach can scale to larger antenna arrays, more sources, or finer resolution bins—and how these techniques apply to frequency estimation, biomedical signal processing, and structural vibration analysis. - **Collaboration Insights from AMD and Fidus:** See how the joint effort leveraged AMD’s latest toolchains and the expertise of Fidus—AMD’s Adaptive Computing Partner of the Year—to validate design flows and deliver a complete reference implementation. **This webinar is ideal for:** - Radar and Wireless  System Architects - FPGA Design and DSP Engineers - Embedded Software Developers - System Architects - VPs of Engineering and Product Development - CTOs and R&D Managers #### Watch the Webinar Recording ![Fidus reverse w orange](https://info.fidus.com/hs-fs/hubfs/Fidus%20reverse%20w%20orange.png?width=120&height=48&name=Fidus%20reverse%20w%20orange.png) © Copyright 2024 Fidus. 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