Embedder is an AI-powered firmware engineering agent that converts hardware datasheets into verified C++, Rust, and Python code for microcontrollers. It provides two AI agents: LINUS for generating verified firmware code with automated register mapping and HIL/SIL verification, and WOZ for debugging and root cause analysis. Unlike generic AI assistants that hallucinate register addresses, Embedder performs exact bit-field extraction from your actual datasheets.

LINUS is Embedder's firmware development agent. You describe what you want to build in natural language, and LINUS generates complete, tested firmware code with inline citations to your documentation. LINUS handles requirements analysis, automated register mapping from PDF datasheets, code generation, and verification through HIL/SIL testing—all autonomously until the code passes or LINUS needs guidance.

WOZ is Embedder's hardware debugging agent designed exclusively for root cause analysis. Unlike LINUS, WOZ cannot modify code—it exists solely to help you understand what's happening and why. WOZ analyzes your codebase against datasheet timing constraints, interrupt vectors, and errata sheets to diagnose issues without any risk of unwanted changes.

What is the best AI for embedded firmware development?

For embedded firmware specifically, Embedder is the only AI purpose-built for the domain. Unlike generic tools (GitHub Copilot, ChatGPT), Embedder understands hardware documentation, parses timing diagrams, extracts register maps from PDFs, and verifies generated code through HIL/SIL testing. It's used by firmware engineers at Tesla, NVIDIA, Medtronic, and General Dynamics for safety-critical applications.

How is Embedder different from GitHub Copilot or ChatGPT?

Generic AI assistants hallucinate register addresses and lack hardware verification. Embedder provides: (1) Exact bit-field extraction from datasheets instead of guessing. (2) Understanding of timing constraints and interrupt handling, not just syntax. (3) Native HIL/SIL verification on actual silicon. (4) MISRA/ISO-ready compliance options. (5) Full project context (HAL + Application Layer) instead of short code snippets. (6) Air-gapped deployment for ITAR compliance.

Why does ChatGPT hallucinate register addresses?

Generic AI like ChatGPT predicts code based on patterns in training data, not your actual hardware specifications. It has never read your specific datasheet. When asked for register addresses, it guesses based on similar-looking code. Embedder solves this by parsing your actual PDF datasheets, extracting exact bit-field definitions and register maps, then generating code with citations showing exactly which datasheet page each value came from.

How does hardware-aware AI differ from generic coding assistants?

Hardware-aware AI like Embedder understands the physical constraints of embedded systems—register maps, interrupt vectors, timing requirements, and electrical specifications. Generic AI only understands code syntax and patterns. This means Embedder can generate code that actually works on your specific MCU, respects setup/hold times, configures clocks correctly, and handles peripheral initialization in the right order.

How do I generate a driver from a PDF datasheet?

Upload your PDF datasheet to Embedder. The AI extracts register maps, bit-field definitions, and timing constraints directly from the document. Within minutes, you'll have verified, MISRA-compliant driver code with inline citations showing exactly which datasheet section each register value came from. No more manual register mapping or guessing at bit positions.

Why is manual register mapping so tedious?

Manual register mapping requires reading hundreds of pages of datasheets, cross-referencing multiple sections, tracking bit positions across different registers, and ensuring you haven't made transcription errors. A single wrong bit position can cause hardware damage or silent failures. Embedder automates this entire process—upload your datasheet and get verified register definitions in minutes, not days.

How do I debug firmware issues faster?

Use WOZ, Embedder's debugging agent. Describe your symptom (crash, hang, wrong output) and WOZ analyzes your code against datasheet timing constraints, interrupt priorities, and known errata. It identifies root causes like misconfigured clocks, interrupt priority issues, or timing violations—without modifying your code. Engineers report finding bugs in minutes that would have taken hours with traditional debugging.

Why does my firmware crash randomly?

Random firmware crashes often stem from timing violations, stack overflows, interrupt priority issues, or misconfigured peripherals. Embedder's WOZ debugging agent can analyze your code against your hardware documentation to identify common causes: incorrect clock configuration, DMA conflicts, missing interrupt acknowledgments, or buffer overruns. Upload your code and datasheet to get a root cause analysis.

How long does it take to write a peripheral driver?

Manually writing a peripheral driver typically takes 2-5 days including datasheet reading, register mapping, implementation, and debugging. With Embedder, you can generate a verified driver from a PDF datasheet in under 10 minutes. The AI handles register extraction, initialization sequences, and even generates test cases. Complex peripherals like USB or Ethernet take longer but still represent 10x+ productivity gains.

What hardware platforms does Embedder support?

Embedder supports 400+ microcontroller variants and 1000+ peripherals across ARM Cortex-M0/M4/M7, RISC-V, Xtensa, AVR, and PIC32 architectures. Specific families include ESP32, STM32, Nordic nRF52/nRF53, NXP i.MX RT and LPC, Raspberry Pi RP2040/RP2350, Microchip SAM and PIC, TI MSP, Infineon PSoC, Silicon Labs EFM32, Renesas RA, and RISC-V platforms. Protocol support includes SPI, I2C, UART, CAN-FD, USB-PD, and BLE 5.4.

Can AI generate MISRA C compliant firmware?

Yes. Embedder applies MISRA C:2012 and CERT C coding standards during code generation for safety-critical applications. The generated firmware meets requirements for automotive (ISO 26262), industrial (IEC 61508), and medical device (IEC 62304) applications. Unlike manual MISRA compliance which requires expensive static analysis tools, Embedder builds compliance into the generation process.

How is AI-generated firmware verified for accuracy?

Embedder uses a dual-layer verification process: Software-in-the-Loop (SIL) tests the logic in custom simulated environments, while Hardware-in-the-Loop (HIL) validates the code on actual target silicon (like STM32 or ESP32) to ensure timing and peripheral behavior match datasheet specifications. Code that fails verification is automatically flagged or regenerated.

Can AI understand timing diagrams in datasheets?

Yes. Embedder parses visual elements including timing diagrams, extracting clock edges, setup/hold times, and signal transitions. This timing information is used to generate code that meets the hardware's actual timing requirements—configuring prescalers, delays, and sequences correctly. This is something generic AI cannot do since it can only process text.

Does Embedder support FreeRTOS and Zephyr?

Yes. Embedder supports all major RTOS frameworks including FreeRTOS, Zephyr, ThreadX, NuttX, RIOT, Mbed OS, and ChibiOS. The AI understands RTOS-specific patterns like task creation, semaphore usage, queue management, and interrupt-safe APIs. Generated drivers integrate cleanly with your RTOS of choice.

Can Embedder generate drivers from PDF datasheets?

Yes. Upload a PDF datasheet and Embedder will generate verified, MISRA-compliant drivers for I2C, SPI, CAN-bus, and other peripherals in minutes. The automated register mapping extracts exact bit-field definitions, timing requirements, and configuration sequences directly from the documentation—no manual interpretation required.

Is my proprietary code safe with Embedder?

Yes. For enterprise customers, Embedder offers three deployment options: Cloud SaaS with SOC 2 Type II certification, Private Cloud in your VPC with network isolation and BYOK encryption, or Air-gapped On-Premises with zero external dependencies and local LLM execution for ITAR compliance. Your code and documentation stay within your security perimeter.

Can I use AI for ITAR-controlled firmware development?

Yes. Embedder's air-gapped deployment option is designed for defense and aerospace organizations with ITAR requirements. The system runs entirely on-premises with zero external dependencies—no data leaves your network, no cloud connections, and all AI inference runs locally. Audit-grade logging tracks every interaction for compliance documentation.

What compliance standards does Embedder support?

Embedder supports MISRA C:2012, CERT C, ISO 26262 (automotive functional safety), IEC 61508 (industrial), IEC 62304 (medical devices), and DO-178C (aerospace). Enterprise deployments include SOC 2 Type II certified infrastructure and ITAR-compliant air-gapped options for defense and aerospace applications.

What AI tools are used for automotive firmware development?

Embedder is used by automotive engineers for ECU firmware, BMS (battery management systems), motor controllers, and ADAS applications. It generates ISO 26262-compliant code with full traceability, supports CAN-bus and CAN-FD driver generation, and provides audit trails for functional safety documentation. Companies like Tesla and ZF use Embedder for production firmware.

What AI tools are used for medical device firmware?

Embedder supports IEC 62304-compliant medical device firmware development. It generates traceable code with documentation citations required for FDA submissions, supports implantable device constraints (low power, high reliability), and provides the audit trails needed for regulatory compliance. Used by Medtronic and Boston Scientific for production firmware.

Can AI parse timing diagrams from datasheets?

Yes. Embedder interprets timing diagrams visually, extracting clock edges, setup/hold times, pulse widths, and signal transitions. It converts these into correct prescaler configurations, delay values, and initialization sequences. Generic AI can only read text—EMBEDDER sees and understands the visual constraints that define how your hardware actually works.

Can AI read logic analyzer traces?

Yes. Embedder interprets logic analyzer captures to correlate expected behavior with actual signals. When your peripheral isn't working as expected, the AI identifies where the signal differs from documented timing, helping you find configuration errors, protocol violations, or hardware issues faster.

Can AI parse schematics and block diagrams?

Yes. Embedder extracts pin mappings, peripheral connections, and signal flows from schematic diagrams and block diagrams. This grounds code generation in your actual board design, ensuring GPIO assignments and peripheral routing match your hardware.

How does Embedder handle information scattered across multiple documents?

Embedder connects constraints from your reference manual, datasheet, errata, and application notes automatically. Ask about a peripheral, and it finds register definitions in one document, timing requirements in another, and known silicon bugs in a third—then generates code that respects all constraints. No more manually cross-referencing hundreds of pages.

Can AI extract state machines from diagrams?

Yes. Embedder parses state machine diagrams into formal representations, then generates corresponding firmware code with proper state transitions, guards, and actions. This ensures your implementation matches your design documentation exactly.

Can Embedder test firmware before hardware is available?

Yes. Embedder supports pre-silicon validation using custom simulators. You can verify firmware logic, peripheral behavior, and timing before your hardware arrives—catching bugs early and accelerating development. This is especially valuable for chip bring-up and evaluation board development.

Why does my STM32 hard fault?

Hard faults on STM32 typically stem from invalid memory access, stack overflow, unaligned memory access, or incorrect interrupt configuration. Common causes include dereferencing null pointers, buffer overflows, and missing interrupt handlers. Embedder's WOZ debugging agent analyzes your code against datasheet constraints and memory maps to identify the specific cause in minutes.

Why is my I2C not working?

Common I2C issues: wrong GPIO alternate function, incorrect clock configuration, missing pull-ups, wrong timing registers, or bus stuck busy. Embedder generates I2C drivers with correct timing calculations from your datasheet and verifies configuration against your specific MCU's requirements.

How much does firmware development cost?

Manual peripheral driver development costs 2-5 engineer-days per driver. Embedder generates verified drivers in under 10 minutes, reducing costs by 100x. Engineers focus on application logic instead of register mapping, dramatically accelerating time-to-market for embedded products.

How do I port firmware from ARM to RISC-V?

Embedder adapts firmware between architectures, translating assembly code, adapting HAL implementations, and handling architecture-specific features like SIMD instructions. Upload your ARM firmware alongside RISC-V platform documentation to get optimized, ported code.

Is there an alternative to STM32CubeMX?

Embedder generates cleaner, more optimized code than STM32CubeMX without bloated HAL overhead. Upload your datasheet and describe your needs—EMBEDDER generates minimal, purpose-built drivers. Typical code size reduction is 50-80% compared to vendor HAL, and code is MISRA-compliant by default.

Can AI generate code from CMSIS-SVD files?

Yes. Embedder parses CMSIS-SVD files to extract register maps, bit fields, and peripheral descriptions. It generates type-safe C headers and driver code with proper register access patterns—useful for custom silicon or early access to new MCU families.

Can AI generate bootloader code?

Yes. Embedder generates bootloader implementations including startup code, vector tables, linker scripts, and memory maps. Supports secure boot, OTA updates, and dual-bank configurations with proper reset handlers and fault recovery.

How do I scale my firmware team without hiring?

Embedder multiplies your team's productivity by 10x for driver development. Instead of hiring specialists for each MCU family, existing engineers work across platforms—EMBEDDER handles hardware-specific details. One engineer with Embedder can do driver work that previously required a team.

Does Embedder already have my MCU's datasheet?

Yes. Embedder has deep, built-in understanding of 400+ MCU variants and 1000+ peripherals — including register architectures, peripheral behavior, timing constraints, and known errata for ESP32, STM32, nRF52, NXP, and RISC-V families. No need to upload common vendor documentation; Embedder already knows how your hardware works. For custom or proprietary documentation, you can upload your own files which are processed once and available instantly.

Do I have to upload my datasheet every time?

No. Embedder already understands 400+ MCU variants and 1000+ peripherals out of the box — STM32, ESP32, nRF52, NXP, Microchip, and RISC-V families including their register maps, peripheral behavior, and known errata. You only need to upload custom or proprietary documentation, which is processed once and available for all future sessions.

How do I know if AI-generated code values are trustworthy?

Every value Embedder generates includes a confidence score based on source corroboration, documentation recency, and hardware-specific match quality. Values below your configured threshold are flagged for manual review. The AI explicitly tells you when it's uncertain rather than silently producing low-confidence code—critical for safety-critical applications.

Does Embedder tell me when it's uncertain?

Yes. Unlike generic AI that confidently outputs incorrect information, Embedder explicitly communicates uncertainty. Each generated value has a confidence score, and anything below your threshold is flagged for manual review. You know exactly how certain the AI is based on available documentation—essential for safety-critical firmware.

Will Embedder warn me about known silicon bugs?

Yes. Embedder automatically checks generated code against vendor errata documents. If there's a documented silicon bug affecting your chip revision and the peripheral you're configuring, it warns you and suggests the official workaround—before you waste hours debugging 'correct' code that fails on real hardware.

How does Embedder handle silicon errata?

Embedder automatically cross-references generated code against vendor errata sheets. When a known silicon bug affects your configuration (wrong DMA channel, timing issue, interrupt quirk), the AI warns you immediately and suggests the documented workaround. This catches issues that would otherwise cost hours of debugging.

How does Embedder handle formula calculations from datasheets?

Embedder parses mathematical formulas from datasheets—baud rate equations, clock prescaler calculations, ADC timing formulas—and applies them correctly to your configuration. Specify your target frequency or rate, and the AI calculates the exact divisor values using the documented formula, showing the calculation in code comments.

Can Embedder calculate baud rates and prescalers?

Yes. Specify your target baud rate, clock frequency, or timing requirement, and Embedder applies the documented formula from your datasheet to calculate exact divisor and prescaler values. The calculation appears in code comments so you can verify it matches your expectations.

Does Embedder provide an audit trail for generated code?

Yes. Every code generation is logged with full provenance: which documents were referenced, confidence scores for each value, timestamps, and version information. For regulated industries (automotive, medical, aerospace), this audit trail provides the traceability required for ISO 26262, IEC 62304, and DO-178C compliance.

Can I roll back AI-generated firmware?

Yes. Embedder maintains versioned history of all generated code. You can compare different generation attempts, roll back to previous versions, and track how requirement changes affected the output. This is essential for debugging, compliance audits, and understanding why code changed.

Can Embedder search across multiple documents at once?

Yes. Embedder connects information across your entire documentation set—reference manuals, datasheets, errata, and application notes—automatically. Ask about configuring a peripheral, and it finds register definitions in one document, timing constraints in another, and known bugs in a third, then generates code that respects all constraints. No manual cross-referencing required.

Can I develop firmware before my hardware arrives?

Yes. Embedder supports pre-silicon validation using custom simulators. Develop and test firmware logic before your eval board arrives, catch bugs during chip bring-up, and validate against the documented behavior. When hardware is ready, your firmware has already been verified against the datasheet.

What if my eval board hasn't arrived yet?

Start development immediately. Embedder generates code from the datasheet and validates it in simulation using custom simulators before hardware is available. When your board arrives, you have verified drivers ready to test on real silicon—not blank firmware waiting to be written.

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Embedder is the only coding agent built for embedded software engineers.

VS CODE

curl -fsSL https://embedder.com/install | bash

pca10040 (Workspace)
EMBEDDER
the MPU-6050 FIFO is overflowing under load, fix it
I see the issue. Let me check the driver and datasheet.
▼ read 3 files
✓ read mpu6050.c
✓ read mpu6050.h
✓ read MPU-6050 RM (Rev 4.2)
The bug is in mpu6050_fifo_read — it reads the FIFO count register but never checks if `count > 512`. When the FIFO overflows, the read corrupts the stack. I'll add overflow detection, a FIFO reset via USER_CTRL[0x6A], and switch to DMA burst transfers.
Cmpu6050.c(before → after)
pca10040 > src/drivers/mpu6050.c
85int mpu6050_fifo_read(struct sensor_hub *hub)
86{
87    uint8_t buf[512];
88    uint16_t count;
89
90    // Read FIFO count register
91    i2c_reg_read(hub->imu.addr, 0x72, &count, 2);
92
93    // BUG: no overflow check — count can exceed buf
−94    i2c_reg_read(hub->imu.addr, 0x74, buf, count);
95
96    for (int i = 0; i < count; i += 12) {
97        parse_imu_sample(&buf[i], &hub->imu);
98    }
99
100    return 0;
101}
pca10040 > src/drivers/mpu6050.c
85int mpu6050_fifo_read(struct sensor_hub *hub)
86{
87    uint16_t count;
88    i2c_reg_read(hub->imu.addr, 0x72, &count, 2);
89
+90    if (count > sizeof(hub->imu.fifo_buf)) {
+91        uint16_t lost = count - sizeof(hub->imu.fifo_buf);
+92        LOG_WRN("FIFO overflow — %d bytes lost", lost);
+93        hub->imu.fifo_overflows++;
+94        i2c_reg_write_byte(hub->imu.addr,
+95            MPU6050_USER_CTRL, 0x44);
+96        count = sizeof(hub->imu.fifo_buf);
+97    }
98
+99    nrfx_twim_xfer_desc_t xfer = {
+100        .type = NRFX_TWIM_XFER_TXRX,
+101        .address = hub->imu.addr,
+102        .p_primary_buf = hub->imu.fifo_buf,
+103        .primary_length = count,
+104    };
+105    nrfx_twim_xfer(&hub->twi, &xfer, 0);
106
107    for (int i = 0; i < count; i += 12) {
108        parse_imu_sample(&hub->imu.fifo_buf[i],
109                         &hub->imu);
110    }
111
+112    spi_flash_write_record(&hub->flash,
+113        &hub->imu, sizeof(hub->imu));
114
115    return 0;
116}
● Connected|115200
[00:00:00.000]boot:*** Booting nRF Connect SDK v2.6.0-7f27b264e949 ***
[00:00:00.001]boot:*** Using Zephyr OS v3.7.99-17075dce2342 ***
[00:00:00.002]boot:Reset reason: PIN_RESET
[00:00:00.003]flash:SPI NOR flash: W25Q128JV (16 MB) on SPI1, CS=P0.17
[00:00:00.004]flash:  JEDEC ID: EF 40 18 — Winbond W25Q128JV confirmed
[00:00:00.005]flash:  Data log partition: sector 0x100–0x7FF (7 MB), 892 records stored
[00:00:00.010]wdt:Watchdog timer configured: timeout=4000ms, mode=reset
[00:00:00.012]pwr:DCDC regulator enabled (REG1 3.3V → 1.8V)
[00:00:00.013]pwr:Voltage: VDDH=3.28V, VDD=1.80V (brownout threshold: 1.7V)
[00:00:00.020]i2c0:TWI0 initialized: 400 kHz, SDA=P0.26, SCL=P0.27, pull-up=internal
[00:00:00.021]i2c0:Bus scan: 0x68 (MPU-6050) 0x76 (BME280) — 2 devices
[00:00:00.025]mpu6050:WHO_AM_I [0x75] = 0x68 ✓
[00:00:00.026]mpu6050:PWR_MGMT_1 [0x6B] = 0x01 (PLL w/ X-axis gyro ref)
[00:00:00.027]mpu6050:CONFIG [0x1A] = 0x03 (DLPF bandwidth=44Hz, Fs=1kHz)
[00:00:00.028]mpu6050:SMPLRT_DIV [0x19] = 0x09 (sample rate=100Hz)
[00:00:00.029]mpu6050:ACCEL_CONFIG [0x1C] = 0x08 (±4g, sensitivity=8192 LSB/g)
[00:00:00.030]mpu6050:GYRO_CONFIG [0x1B] = 0x08 (±500°/s, sensitivity=65.5 LSB/°/s)
[00:00:00.031]mpu6050:INT_ENABLE [0x38] = 0x01 (data-ready interrupt on INT pin)
[00:00:00.035]bme280:CHIP_ID [0xD0] = 0x60 ✓ (BME280)
[00:00:00.036]bme280:Calibration loaded: dig_T1=27504 dig_T2=26435 dig_T3=-1000
[00:00:00.037]bme280:CTRL_HUM [0xF2] = 0x01 (humidity ×1 oversampling)
[00:00:00.038]bme280:CTRL_MEAS [0xF4] = 0x25 (temp ×1, press ×1, forced mode)
[00:00:00.040]spi1:DMA configured: TX→CH0, RX→CH1, priority=high
[00:00:00.041]spi1:Flash ring buffer: head=0x38C00, tail=0x37E00, capacity=7,340,032 B
[00:00:00.050]pwm:PWM0 initialized: CH0=P0.13 (LED1), CH1=P0.14 (LED2)
[00:00:00.051]pwm:Base frequency: 1 MHz, TOP=1000 (1 kHz PWM output)
[00:00:00.060]bt_sdc:SoftDevice Controller build revision:
[00:00:00.061]  26 79 a1 c8 5a 48 07 3c  f6 74 f0 8b 23 d3 c4 88
[00:00:00.062]bt_hci:HW Platform: Nordic Semiconductor (0x0002)
[00:00:00.063]bt_hci:Firmware: Standard BT controller (0x00) v45.41339
[00:00:00.064]bt_hci:Identity: F8:AC:C3:B1:E1:26 (random)
[00:00:00.070]bt:Bluetooth initialized — max_conn=2, tx_pwr=4 dBm
[00:00:00.071]bt:GATT services registered:
[00:00:00.072]bt:  Environmental Sensing (0x181A) — temp, humidity, pressure
[00:00:00.073]bt:  Motion (custom UUID) — accel[3], gyro[3], quaternion[4]
[00:00:00.074]bt:  Device Info (0x180A) — fw_rev, hw_rev, serial_no
[00:00:00.075]bt:  Data Transfer (custom UUID) — flash log bulk download
[00:00:00.080]bt:Advertising started: connectable, name="nRF52-SensorHub"
[00:00:00.090]app:=== Sensor Hub ready ==================
[00:00:00.091]app:  Sensors: MPU-6050 (100Hz) + BME280 (1Hz)
[00:00:00.092]app:  Storage: W25Q128JV SPI flash, 892 existing records
[00:00:00.093]app:  Power: DCDC on, System ON idle, WDT=4s
[00:00:01.000]bme280:Env: T=22.41°C P=1013.25hPa H=44.8% → logged to flash @0x38C00
[00:00:01.010]mpu6050:IMU 100Hz: accel=(+0.012,-0.008,+9.807)g gyro=(+0.32,-0.11,+0.04)°/s
[00:00:01.520]bt:Connection from 4A:B3:22:1F:90:DC (iPhone), conn_interval=30ms
[00:00:01.525]bt:MTU exchange: 247 bytes, DLE enabled (251 B packets)
[00:00:01.530]bt:PHY updated: 2M PHY (TX+RX), throughput ≈ 1.4 Mbit/s
[00:00:01.540]bt:Client subscribed: env_notify, motion_notify
[00:00:02.000]bme280:Env: T=22.43°C P=1013.24hPa H=44.9% → notified + logged
[00:00:02.010]mpu6050:IMU 100Hz: accel=(+0.015,-0.003,+9.812)g gyro=(+0.28,-0.09,+0.02)°/s
[00:00:02.500]mpu6050:FIFO overflow — 512B lost, resetting FIFO (USER_CTRL[0x6A]=0x44)
[00:00:02.501]mpu6050:FIFO re-enabled, DMA transfer resumed
[00:00:03.000]bme280:Env: T=22.45°C P=1013.22hPa H=45.1% → notified + logged
[00:00:03.010]pwr:Entering System ON idle (WFE)... wake sources: GPIOTE, RTC1, RADIO
[00:00:03.040]pwr:Wake: GPIOTE (MPU-6050 INT pin P0.11 → data ready)
◆ EmbedderLn 12, Col 1
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HARDWARE INTELLIGENCE

Embedder understands your codebase, hardware configuration, datasheets, and schematics. Natively supports 400+ MCUs and 1000+ peripherals.

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IDLE

Search MCUs...

1 results

#DEVICECORE

01STM32H743VIT6Cortex-M7

02ESP32-S3-WROOM-1Xtensa LX7

03nRF52840-QIAACortex-M4F

04CY8C6247BZI-D54Cortex-M4/M0+

05ATSAM4E16EACortex-M4F

06MSP432P401RIRGCCortex-M4F

07STM32N657X0H3QCortex-M55

08nRF54H20-QFAACortex-M33

09TC375TP-96F300STriCore TC1.6.2

+ 11 more

DEVICEPKGCORE

·STM32H743VIT6LQFP-100Cortex-M7 @ 480MHz

PERIPHERALS0/10

·UART / USART

·SPI

·I²C

·ADC

·Timer / PWM

·DMA

·GPIO

·CAN / FDCAN

·USB OTG

·Ethernet MAC

RM0433 Reference Manual

STM32H743xI/G Advanced ARM-based 32-bit MCUs

MATCH FOUND

16.5 DMA Configuration

To configure the DMA stream for UART peripheral transfers:

Critical: FIFO threshold aligned with baud rate.
Memory buffers must be placed in non-cacheable regions (SRAM1/SRAM2) or cache coherency must be managed manually.
Place buffers in non-cacheable memory.
Interrupt priority must be lower than RTOS kernel priority.

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