IoT Test Chips and Boards

Arm create a range of boards, which are built around Arm-developed test chips. These boards enable easier development or evaluation of the Arm IP in real-life conditions. The Arm powered IoT test chips are based on subsystem IP, which offer a foundation for your future designs.

Some use cases for these IoT boards include:

  • Simplified integration of Arm TrustZone security technology for software developers, by getting a realistic Armv8-M development platform (Musca only)
  • Improved understanding of the trade-offs and performance of the IP, inside the SoC for hardware designers
  • SoC architects can use the test chips as reference for their future products
  • Product companies could these IoT boards to make progress on software before the final silicon is available
  • Partners can use them to demonstrate complementary IP in a system context

Three boards containing Arm IoT test chips are currently available:

Musca-A Test Chip

The Arm Musca-A board is based on the latest Arm Corelink SSE-200 Subsystem featuring two Arm Cortex-M33 processors. This board is the first Platform Security Architecture (PSA) development platform.

This design extends the Arm TrustZone architecture, from the processors to the whole system and utilizes the Arm TrustZone CryptoCell-312. This means that developers can use the latest security technology to implement the best protection for IoT devices.

Arm Musca-A1 development board

 

 

Musca-B1 Test Chip

The Musca-B1 test chip board is an evaluation platform to develop PSA-ready IoT Subsystems for Cortex-M, based on the Armv8-M architecture. It is built on the Platform Security Architecture (PSA) principles and introduces additional security features, such as CryptoIsland and eFlash.





The development board image of the Musca-B1 test chip.

Beetle IoT Evaluation Platform

The Arm Beetle board is based on the Arm CoreLink SSE-100 Subsystem, which features the Arm Cortex-M3 processor. This is a great example of a design containing embedded Flash, a cache and Bluetooth radio.

Use the Mbed OS software framework to build IoT applications.



    


Get support

Arm support

Arm training courses and on-site system-design advisory services enable licensees to realize maximum system performance with lowest risk and fastest time-to-market.

Arm training courses   Open a support case

Community Forums

Suggested answer FVP License
  • AEMv8 FVP
0 votes 95 views 2 replies Latest yesterday by Bill M Answer this
Not answered How to get the required FLOPs for my neural network
  • Deep Learning
0 votes 36 views 0 replies Started yesterday by fset89 Answer this
Suggested answer GCC 7.2.1 on Cortex-M4 - C++ exceptions not being caught
  • Interrupt Handling
  • GCC
  • GNU
  • Cortex-M4
0 votes 981 views 2 replies Latest 2 days ago by David R. Answer this
Not answered GCC g++ version 8 very slow to compile 0 votes 76 views 0 replies Started 8 days ago by Terry Barnaby Answer this
Not answered Arm Graphics Analyzer 0 votes 78 views 0 replies Started 8 days ago by mgupt Answer this
Answered Save tensorflow model for ArmNN
  • Machine Learning (ML)
  • TensorFlow
  • Arm NN
0 votes 260 views 3 replies Latest 8 days ago by GeraldK Answer this
Suggested answer FVP License Latest yesterday by Bill M 2 replies 95 views
Not answered How to get the required FLOPs for my neural network Started yesterday by fset89 0 replies 36 views
Suggested answer GCC 7.2.1 on Cortex-M4 - C++ exceptions not being caught Latest 2 days ago by David R. 2 replies 981 views
Not answered GCC g++ version 8 very slow to compile Started 8 days ago by Terry Barnaby 0 replies 76 views
Not answered Arm Graphics Analyzer Started 8 days ago by mgupt 0 replies 78 views
Answered Save tensorflow model for ArmNN Latest 8 days ago by GeraldK 3 replies 260 views