 My name is Ram Kumar Yadavalli and I'm a Product Marketing Engineer at ST Microelectronics. In this presentation, I'm going to show you building blocks of STM32H7 product line to build graphics, AI, and voice UI applications along with the demonstration. Here is STM32H7 product portfolio. As you see here, we recently introduced two new products, the STM32H7A and STM32H7B. These two embed larger internal RAM of 1.4 megabytes targeting graphics applications. On the top right, you notice two dual-core STM32H7 product line. Also in the middle, we show you the three single-core variants. All of these products are in production right now with ST's 10-year longevity commitment to all STM32 product lines. As you see in graph with dual-core STM32H7 product line, we made a performance record of 3,224 combined-core mark number between the two cores. And these products embed 2 megabytes of internal flash and 1 megabyte of internal RAM. With this strict performance and larger internal memories, this product line is well positioned for voice UI and cloud-connected solutions. On this STM32H7 single-core lineup, we achieved performance record of 2,424 core mark with M7 core and this lineup has 2 megabytes of internal flash and 1 megabyte of internal RAM and can run up to 480 megabytes. This newly introduced single-core lineup is targeted for graphics applications because they increased internal RAM of up to 1.4 megabytes. Product variants in this lineup are going to be in production from July 2020. And this lineup has graphics supported even on a 64-pin QFP package. Here is a typical use case for dual-core STM32H7 product line. Designers can use M7 core to run AI neural network to predict failures and display motor diagnostics while the M4 core performs a real-time control on motors based on sensor feedback along with cloud connectivity. The two cores run independently and share data using hardware mailboxes. Here is a human-machine interface use case built around a single-core STM32H7. On this product line, the designers have 1.4 megabytes of internal RAM. Of this huge memory, 1 megabyte is contiguous memory to map to large frame buffer size supporting up to XGA resolution. In addition to this large internal memory, the hardware designers have wide choice of on-chip embedded memory controllers like Octol Spy, EMMC and SD card. Here is a table to show how a designer can achieve up to XGA resolution using only internal memory with double-frame architecture on STM32H7A series microcontrollers. If your use case is to build professional-quality smartphone-like graphics UI on an embedded device like our STM32H7 product line, ST provides free state-of-the-art graphics tool suite known as TADGFX. This is widely known tool chain used by many partners on embedded devices that are in production right now. TADGFX is offered as an add-on tool in the STM32 ecosystem for fast, easy prototyping and development on your preferred display in the STM32 portfolio. Here is another use case. If you'd like to add natural language, cloud-based voice UI, on a low-cost embedded controller such as STM32H7, we have application solutions combining audio acquisition, voice processing along with cloud connectivity stack, running on a single chip. These solutions support far-field, local wayquired processing with powerful audio front-end framework. With all these and with embedded crypto and secure firmware upgrade solution, brings the designer a very cost-effective solution. Let's take a look at STM32H7 demonstration right now. Here I'm showing you an application demonstration running on dual-core STM32H757 microcontroller. You're seeing the Product Evaluation Board running the demonstration that shows five video objects. Of these, four are MJPEG video streams that run in parallel along with another video of computational intensive fractal module. As you see here on display to the left-hand side, you can see four MJPEG video streams that are running at a frame rate of 30 frames per second approximately. To the right on the display, you see a video object of fractal competition running at a frame rate of 14 frames per second approximately. Currently both cores M7 and M4 are working. When both cores are running, you can see the CPU load and this is shown on the right-hand bottom corner. It shows a load of Cortex M7 which is approximately 19%. The demo shows the differences using a dual-core versus a single-core and so I will now turn off one of the cores, the Cortex M4 core. As you see after turning off the M4 core, the display shows that the Cortex M7 core alone is continuing to decode and display all five video objects. Also as you can understand, the CPU load on the M7 to go up and this is now 52% approximately. Now to let both cores run and share the load, I will now turn on the Cortex M4 core. Since we have both cores running now, the processing on M7 core dropped back to 20%. This demonstrates how designers can take benefit of dual cores of STM32H757 such as the flexibility to switch processing between two cores and to share load depending on the end use case. The two cores on this product run independently and share the data via mailbox hardware. Thank you very much for your attention and for more information on STM32H7, please go to www.st.com or what slash STM32H7. Thank you.