SPRACW5A April   2021  – December 2021 F29H850TU , F29H859TU-Q1 , TMS320F2800132 , TMS320F2800133 , TMS320F2800135 , TMS320F2800137 , TMS320F280021 , TMS320F280021-Q1 , TMS320F280023 , TMS320F280023-Q1 , TMS320F280023C , TMS320F280025 , TMS320F280025-Q1 , TMS320F280025C , TMS320F280025C-Q1 , TMS320F280033 , TMS320F280034 , TMS320F280034-Q1 , TMS320F280036-Q1 , TMS320F280036C-Q1 , TMS320F280037 , TMS320F280037-Q1 , TMS320F280037C , TMS320F280037C-Q1 , TMS320F280038-Q1 , TMS320F280038C-Q1 , TMS320F280039 , TMS320F280039-Q1 , TMS320F280039C , TMS320F280039C-Q1 , TMS320F280040-Q1 , TMS320F280040C-Q1 , TMS320F280041 , TMS320F280041-Q1 , TMS320F280041C , TMS320F280041C-Q1 , TMS320F280045 , TMS320F280048-Q1 , TMS320F280048C-Q1 , TMS320F280049 , TMS320F280049-Q1 , TMS320F280049C , TMS320F280049C-Q1 , TMS320F28075 , TMS320F28075-Q1 , TMS320F28076 , TMS320F28374D , TMS320F28374S , TMS320F28375D , TMS320F28375S , TMS320F28375S-Q1 , TMS320F28376D , TMS320F28376S , TMS320F28377D , TMS320F28377D-EP , TMS320F28377D-Q1 , TMS320F28377S , TMS320F28377S-Q1 , TMS320F28378D , TMS320F28378S , TMS320F28379D , TMS320F28379D-Q1 , TMS320F28379S , TMS320F28384D , TMS320F28384D-Q1 , TMS320F28384S , TMS320F28384S-Q1 , TMS320F28386D , TMS320F28386D-Q1 , TMS320F28386S , TMS320F28386S-Q1 , TMS320F28388D , TMS320F28388S , TMS320F28P650DH , TMS320F28P650DK , TMS320F28P650SH , TMS320F28P650SK , TMS320F28P659DH-Q1 , TMS320F28P659DK-Q1 , TMS320F28P659SH-Q1

 

  1.   Trademarks
  2. 1Introduction
  3. 2ACI Motor Control Benchmark Application
    1. 2.1 Source Code
    2. 2.2 CCS Project for TMS320F28004x
    3. 2.3 CCS Project for TMS320F2837x
    4. 2.4 Validate Application Behavior
    5. 2.5 Benchmarking Methodology
      1. 2.5.1 Details of Benchmarking With Counters
    6. 2.6 ERAD Module for Profiling Application
  4. 3Real-time Benchmark Data Analysis
    1. 3.1 ADC Interrupt Response Latency
    2. 3.2 Peripheral Access
    3. 3.3 TMU (math enhancement) Impact
    4. 3.4 Flash Performance
    5. 3.5 Control Law Accelerator (CLA)
      1. 3.5.1 Full Signal Chain Execution on CLA
        1. 3.5.1.1 CLA ADC Interrupt Response Latency
        2. 3.5.1.2 CLA Peripheral Access
        3. 3.5.1.3 CLA Trigonometric Math Compute
      2. 3.5.2 Offloading Compute to CLA
  5. 4C2000 Value Proposition
    1. 4.1 Efficient Signal Chain Execution With Better Real-Time Response Than Higher Computational MIPS Devices
    2. 4.2 Excellent Real-Time Interrupt Response With Low Latency
    3. 4.3 Tight Peripheral Integration That Scales Applications With Large Number of Peripheral Accesses
    4. 4.4 Best in Class Trigonometric Math Engine
    5. 4.5 Versatile Performance Boosting Compute Engine (CLA)
    6. 4.6 Deterministic Execution due to Low Execution Variance
  6. 5Summary
  7. 6References
  8. 7Revision History

4 C2000 Value Proposition

The ACI motor control benchmarking application is self-contained and does not require any special external hardware to execute. Hence, this application can be easily ported to any device to evaluate real-time control performance. A multi-device analysis demonstrates that the C2000 platform offers a rich feature set with an optimized architecture which leads to excellent performance across the real-time signal chain.

Note:
  1. The multi-device analysis for TI C2000 and Competition A and B devices presented in this chapter is based on actual measured data compiled by TI internally in 2021 with ACI motor benchmark example in C2000Ware 3.04.00.00 ported to these devices.
  2. All of the measurements were performed by setting the tool chain to compile code for maximum performance/speed and operating the devices at the maximum CPU frequency.
  3. The cycles/time was measured for each of the devices and the numbers were compared against the F28004x executing from RAM to determine relative performance. The relative performance is represented in each of the graphs and this is why F28004x is marked as "Reference" and is always 1.0.
  4. In the graphs, a lower relative number indicates fewer cycles or lesser time and hence better performance.
  5. The classification of the categories in the graph as "Entry/Mid performance" and "High performance" is based on TI nomenclature. The competition devices are placed in the same category as the TI device that competes with the competition device.