Coral System-on-Module (SoM) – 2GB RAM Version

PRODUCT DETAILS

Attention

This product has shipping restriction to certain countries. It can only be sent to countries and regions listed as below: United States, Japan, Korea, Hong Kong, Taiwan, Australia, New Zealand, India, Ghana, Singapore , Oman, Philippines, Thailand, Austria, Belgium, Bulgaria, Croatia, Cyprus, Denmark, Estonia, Fiji, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom, Switzerland, Iceland, Liechtenstein, Norway, Turkey

Features

  • Provides a complete system: The Coral SoM is a fully-integrated Linux system that includes NXP’s iMX8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, and the Edge TPU coprocessor for ML acceleration. It runs a derivative of Debian Linux we call Mendel.
  • Performs high-speed ML inferencing: The onboard Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 400 FPS, in a power-efficient manner.
  • Integrates with your custom hardware: The SoM connects to your own baseboard hardware with three 100-pin connectors.
  • Supports TensorFlow Lite: No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.
  • Supports AutoML Vision EdgeEasily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge

Description

The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded devices that demand fast machine learning (ML) inferencing. It contains NXP’s iMX 8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google’s Edge TPU coprocessor for high-speed machine learning inferencing.

The Edge TPU is a small ASIC designed by Google that provides high-performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power-efficient manner. This on-device processing reduces latency, increases data privacy, and removes the need for a high-bandwidth connection used to perform ML inferencing in the cloud.

Key benefits of the SoM:

  • High-speed and low-power ML inferencing (4 TOPS @2 W)
  • A complete Linux system (running Mendel, a Debian derivative)
  • Small footprint (40 x 48 mm)

The SoM is also included in the Coral Dev Board, which is a single-board computer that enables fast prototyping and evaluation of the standalone SoM.

Specifications

  • NXP i.MX 8M SoC
    • Quad-core ARM Cortex-A53, plus Cortex-M4F
    • 2D/3D Vivante GC7000 Lite GPU and VPU
  • Google Edge TPU ML accelerator
  • Cryptographic coprocessor
  • Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5 GHz)
  • Bluetooth 4.2
  • 8GB eMMC
  • 2GB LPDDR4
  • USB 3.0
  • Gigabit Ethernet
  • HDMI and MIPI-DSI
  • MIPI-CSI-2
  • Up to 95x GPIO (including SPI, I2C, PWM, UART, SAI, and SDIO)
Feature Details
Main system-on-chip (i.MX8M)
Arm Cortex-A53 MPCore platform Quad symmetric Cortex-A53 processors:

  • 32 KB L1 Instruction Cache
  • 32 KB L1 Data Cache
  • Support L1 cache RAMs protection with parity/ECC

Support of 64-bit Armv8-A architecture:

  • 1 MB unified L2 cache
  • Support L2 cache RAMs protection with ECC
  • Frequency of 1.5 GHz
Arm Cortex-M4 core platform
  • 16 KB L1 Instruction Cache
  • 16 KB L1 Data Cache
  • 256 KB tightly coupled memory (TCM)
Graphic Processing Unit (GPU)
  • Vivante GC7000Lite
  • 4 shaders
  • 267 million triangles/sec
  • 1.6 Gigapixel/sec
  • 32 GFLOPs 32-bit or 64 GFLOPs 16-bit
  • Supports OpenGL ES 1.1, 2.0, 3.0, 3.1, Open CL 1.2, and Vulkan
Video Processing Unit (VPU)
  • 4Kp60 HEVC/H.265 main, and main 10 decoder
  • 4Kp60 VP9 and 4Kp30 AVC/H.264 decoder (requires full system resources)
  • 1080p60 MPEG-2, MPEG-4p2, VC-1, VP8, RV9, AVS, MJPEG, H.263 decoder
I/O connectivity
  • 2x USB 3.0/2.0 controllers with integrated PHY interfaces
  • 1x Ultra Secure Digital Host Controller (uSDHC) interfaces
  • 1x Gigabit Ethernet controller with support for EEE, Ethernet AVB, and IEEE 1588
  • 2x UART modules
  • 2x I2C modules
  • 2x SPI modules
  • 16x GPIO lines with interrupt capability
  • 4x PWM lines
  • Input/output multiplexing controller (IOMUXC) to provide centralized pad control

Note: The list above is the number of signals available to the baseboard (after considering SoC signals used by the SoM).

On-chip memory
  • Boot ROM (128 KB)
  • On-chip RAM (128 KB + 32 KB)
External memory
  • 32/16-bit DRAM interface: LPDDR4-3200, DDR4-2400, DDR3L-1600
  • 8-bit NAND-Flash
  • eMMC 5.0 Flash
  • SPI NOR Flash
  • QuadSPI Flash with support for XIP
Display HDMI Display Interface:

  • HDMI 2.0a supporting one display up to 1080p
  • Upscale and downscale between 4K and HD video (requires full system resources)
  • 20+ Audio interfaces 32-bit @ 384 kHz fs, with Time Division Multiplexing (TDM) support
  • SPDIF input and output
  • Audio Return Channel (ARC) on HDMI

MIPI-DSI Display Interface:

  • MIPI-DSI 4 channels supporting one display, resolution up to 1920 x 1080 at 60 Hz
  • LCDIF display controller
  • Output can be LCDIF output or DC display controller output
Audio
  • 1x SPDIF input and output
  • 2x synchronous audio interface (SAI) modules supporting I2S, AC97, TDM, and codec/DSP interfaces
  • 1x SAI for 8 Tx channels for HDMI output audio
  • 1x SPDIF input for HDMI ARC input
Camera
  • 2x MIPI-CSI2 camera inputs (4-lane each)
Security
  • Resource Domain Controller (RDC) supports four domains and up to eight regions
  • Arm TrustZone (TZ) architecture
  • On-chip RAM (OCRAM) secure region protection using OCRAM controller
  • High Assurance Boot (HAB)
  • Cryptographic acceleration and assurance (CAAM) module
  • Secure non-volatile storage (SNVS): Secure real-time clock (RTC)
  • Secure JTAG controller (SJC)
ML accelerator
Edge TPU coprocessor
  • ASIC designed by Google that provides high-performance ML inferencing for TensorFlow Lite models
  • Uses PCIe and I2C/GPIO to interface with the iMX8M SoC
  • 4 trillion operations per second (TOPS)
  • 2 TOPS per watt
Memory and storage
Random-access memory (SDRAM)
  • 2 GB LPDDR4 SDRAM (4-channel, 32-bit bus width)
  • 1600 MHz maximum DDR clock
  • Interfaces directly to the iMX8M build-in DDR controller
Flash memory (eMMC)
  • 8 GB NAND eMMC flash memory
  • 8-bits MMC mode
  • Conforms to JEDEC version 5.0 and 5.1
Expandable flash (MicroSD)
  • Meets SD/SDIO 3.0 standard
  • Runs at 4-bits SDIO mode
  • Supports system boot from SD card
Network & wireless
Ethernet
  • 10/100/1000 Mbps Ethernet/IEEE 802.3 networks
  • Reduced gigabit media-independent interface (RGMII)
Wi-Fi Murata LBEE5U91CQ module:

  • Wi-Fi 2×2 MIMO (802.11a/b/g/n/ac 2.4/5 GHz)
  • Supports PCIe host interface for W-LAN
Bluetooth Murata LBEE5U91CQ module:

  • Bluetooth 4.2 (supports Bluetooth low-energy)
  • Supports UART interface
Security
Cryptographic coprocessor Microchip ATECC608A cryptographic coprocessor:

  • Asymmetric (public/private) key cryptographic signature solution based on Elliptic Curve Cryptography and ECDSA signature protocols
Hardware interface
Baseboard connectors 3x 100-pin connectors (Hirose DF40C-100DP-0.4V)
Antenna connectors 2x coaxial cable connectors (Murata MM8930-2600)

Block Diagrams

Block diagram of the SoM components

Block diagram of the i.MX8M SoC components, provided by NXP 

Dimensions

Part List

1 x Coral System-on-Module (SoM) – 2GB RAM Version

ECCN/HTS

HSCODE 8543709990
USHSCODE 8473301140
UPC

Coral System-on-Module (SoM) – 2GB RAM Version

$114.99

The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded devices that demand fast machine learning (ML) inferencing. It contains NXP’s iMX 8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google’s Edge TPU coprocessor for high-speed machine learning inferencing.

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Coral System-on-Module (SoM) – 2GB RAM Version

$114.99

The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded devices that demand fast machine learning (ML) inferencing. It contains NXP’s iMX 8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google’s Edge TPU coprocessor for high-speed machine learning inferencing.

View cart

PRODUCT DETAILS

Attention

This product has shipping restriction to certain countries. It can only be sent to countries and regions listed as below: United States, Japan, Korea, Hong Kong, Taiwan, Australia, New Zealand, India, Ghana, Singapore , Oman, Philippines, Thailand, Austria, Belgium, Bulgaria, Croatia, Cyprus, Denmark, Estonia, Fiji, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom, Switzerland, Iceland, Liechtenstein, Norway, Turkey

Features

  • Provides a complete system: The Coral SoM is a fully-integrated Linux system that includes NXP’s iMX8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, and the Edge TPU coprocessor for ML acceleration. It runs a derivative of Debian Linux we call Mendel.
  • Performs high-speed ML inferencing: The onboard Edge TPU coprocessor is capable of performing 4 trillion operations (tera-operations) per second (TOPS), using 0.5 watts for each TOPS (2 TOPS per watt). For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at 400 FPS, in a power-efficient manner.
  • Integrates with your custom hardware: The SoM connects to your own baseboard hardware with three 100-pin connectors.
  • Supports TensorFlow Lite: No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU.
  • Supports AutoML Vision EdgeEasily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge

Description

The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded devices that demand fast machine learning (ML) inferencing. It contains NXP’s iMX 8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google’s Edge TPU coprocessor for high-speed machine learning inferencing.

The Edge TPU is a small ASIC designed by Google that provides high-performance ML inferencing with a low power cost. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power-efficient manner. This on-device processing reduces latency, increases data privacy, and removes the need for a high-bandwidth connection used to perform ML inferencing in the cloud.

Key benefits of the SoM:

  • High-speed and low-power ML inferencing (4 TOPS @2 W)
  • A complete Linux system (running Mendel, a Debian derivative)
  • Small footprint (40 x 48 mm)

The SoM is also included in the Coral Dev Board, which is a single-board computer that enables fast prototyping and evaluation of the standalone SoM.

Specifications

  • NXP i.MX 8M SoC
    • Quad-core ARM Cortex-A53, plus Cortex-M4F
    • 2D/3D Vivante GC7000 Lite GPU and VPU
  • Google Edge TPU ML accelerator
  • Cryptographic coprocessor
  • Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5 GHz)
  • Bluetooth 4.2
  • 8GB eMMC
  • 2GB LPDDR4
  • USB 3.0
  • Gigabit Ethernet
  • HDMI and MIPI-DSI
  • MIPI-CSI-2
  • Up to 95x GPIO (including SPI, I2C, PWM, UART, SAI, and SDIO)
Feature Details
Main system-on-chip (i.MX8M)
Arm Cortex-A53 MPCore platform Quad symmetric Cortex-A53 processors:

  • 32 KB L1 Instruction Cache
  • 32 KB L1 Data Cache
  • Support L1 cache RAMs protection with parity/ECC

Support of 64-bit Armv8-A architecture:

  • 1 MB unified L2 cache
  • Support L2 cache RAMs protection with ECC
  • Frequency of 1.5 GHz
Arm Cortex-M4 core platform
  • 16 KB L1 Instruction Cache
  • 16 KB L1 Data Cache
  • 256 KB tightly coupled memory (TCM)
Graphic Processing Unit (GPU)
  • Vivante GC7000Lite
  • 4 shaders
  • 267 million triangles/sec
  • 1.6 Gigapixel/sec
  • 32 GFLOPs 32-bit or 64 GFLOPs 16-bit
  • Supports OpenGL ES 1.1, 2.0, 3.0, 3.1, Open CL 1.2, and Vulkan
Video Processing Unit (VPU)
  • 4Kp60 HEVC/H.265 main, and main 10 decoder
  • 4Kp60 VP9 and 4Kp30 AVC/H.264 decoder (requires full system resources)
  • 1080p60 MPEG-2, MPEG-4p2, VC-1, VP8, RV9, AVS, MJPEG, H.263 decoder
I/O connectivity
  • 2x USB 3.0/2.0 controllers with integrated PHY interfaces
  • 1x Ultra Secure Digital Host Controller (uSDHC) interfaces
  • 1x Gigabit Ethernet controller with support for EEE, Ethernet AVB, and IEEE 1588
  • 2x UART modules
  • 2x I2C modules
  • 2x SPI modules
  • 16x GPIO lines with interrupt capability
  • 4x PWM lines
  • Input/output multiplexing controller (IOMUXC) to provide centralized pad control

Note: The list above is the number of signals available to the baseboard (after considering SoC signals used by the SoM).

On-chip memory
  • Boot ROM (128 KB)
  • On-chip RAM (128 KB + 32 KB)
External memory
  • 32/16-bit DRAM interface: LPDDR4-3200, DDR4-2400, DDR3L-1600
  • 8-bit NAND-Flash
  • eMMC 5.0 Flash
  • SPI NOR Flash
  • QuadSPI Flash with support for XIP
Display HDMI Display Interface:

  • HDMI 2.0a supporting one display up to 1080p
  • Upscale and downscale between 4K and HD video (requires full system resources)
  • 20+ Audio interfaces 32-bit @ 384 kHz fs, with Time Division Multiplexing (TDM) support
  • SPDIF input and output
  • Audio Return Channel (ARC) on HDMI

MIPI-DSI Display Interface:

  • MIPI-DSI 4 channels supporting one display, resolution up to 1920 x 1080 at 60 Hz
  • LCDIF display controller
  • Output can be LCDIF output or DC display controller output
Audio
  • 1x SPDIF input and output
  • 2x synchronous audio interface (SAI) modules supporting I2S, AC97, TDM, and codec/DSP interfaces
  • 1x SAI for 8 Tx channels for HDMI output audio
  • 1x SPDIF input for HDMI ARC input
Camera
  • 2x MIPI-CSI2 camera inputs (4-lane each)
Security
  • Resource Domain Controller (RDC) supports four domains and up to eight regions
  • Arm TrustZone (TZ) architecture
  • On-chip RAM (OCRAM) secure region protection using OCRAM controller
  • High Assurance Boot (HAB)
  • Cryptographic acceleration and assurance (CAAM) module
  • Secure non-volatile storage (SNVS): Secure real-time clock (RTC)
  • Secure JTAG controller (SJC)
ML accelerator
Edge TPU coprocessor
  • ASIC designed by Google that provides high-performance ML inferencing for TensorFlow Lite models
  • Uses PCIe and I2C/GPIO to interface with the iMX8M SoC
  • 4 trillion operations per second (TOPS)
  • 2 TOPS per watt
Memory and storage
Random-access memory (SDRAM)
  • 2 GB LPDDR4 SDRAM (4-channel, 32-bit bus width)
  • 1600 MHz maximum DDR clock
  • Interfaces directly to the iMX8M build-in DDR controller
Flash memory (eMMC)
  • 8 GB NAND eMMC flash memory
  • 8-bits MMC mode
  • Conforms to JEDEC version 5.0 and 5.1
Expandable flash (MicroSD)
  • Meets SD/SDIO 3.0 standard
  • Runs at 4-bits SDIO mode
  • Supports system boot from SD card
Network & wireless
Ethernet
  • 10/100/1000 Mbps Ethernet/IEEE 802.3 networks
  • Reduced gigabit media-independent interface (RGMII)
Wi-Fi Murata LBEE5U91CQ module:

  • Wi-Fi 2×2 MIMO (802.11a/b/g/n/ac 2.4/5 GHz)
  • Supports PCIe host interface for W-LAN
Bluetooth Murata LBEE5U91CQ module:

  • Bluetooth 4.2 (supports Bluetooth low-energy)
  • Supports UART interface
Security
Cryptographic coprocessor Microchip ATECC608A cryptographic coprocessor:

  • Asymmetric (public/private) key cryptographic signature solution based on Elliptic Curve Cryptography and ECDSA signature protocols
Hardware interface
Baseboard connectors 3x 100-pin connectors (Hirose DF40C-100DP-0.4V)
Antenna connectors 2x coaxial cable connectors (Murata MM8930-2600)

Block Diagrams

Block diagram of the SoM components

Block diagram of the i.MX8M SoC components, provided by NXP 

Dimensions

Part List

1 x Coral System-on-Module (SoM) – 2GB RAM Version

ECCN/HTS

HSCODE 8543709990
USHSCODE 8473301140
UPC