Cortex-R52 CoreMark Performance Discrepancy Between GCC and IAR Compilers
The Cortex-R52 is a highly efficient real-time processor designed for safety-critical applications, offering a balance between performance and power efficiency. One of the key metrics used to evaluate the performance of such processors is CoreMark, a benchmark that measures the efficiency of a processor’s core in executing common tasks. The Cortex-R52 is advertised with a CoreMark performance score of 4.3 CoreMark/MHz. However, users have reported discrepancies in achieving this score, particularly when using different compilers. Specifically, the GCC compiler yields a CoreMark score of 3.7 CoreMark/MHz, while the IAR compiler achieves the advertised 4.3 CoreMark/MHz. This discrepancy raises questions about the impact of compiler choice, optimization flags, and the use of Tightly Coupled Memory (TCM) on the Cortex-R52’s performance.
The CoreMark benchmark is designed to test the processor’s ability to execute a variety of tasks, including list processing, matrix manipulation, and state machine operations. The benchmark is highly sensitive to compiler optimizations, memory access patterns, and the efficiency of the processor’s pipeline. The Cortex-R52, with its dual-issue superscalar architecture and support for TCM, is capable of achieving high CoreMark scores, but only if the software is optimized to take full advantage of its features. The difference in CoreMark scores between GCC and IAR suggests that the IAR compiler is better at leveraging the Cortex-R52’s architectural features, such as TCM and advanced pipeline optimizations.
The use of TCM is particularly relevant in this context. TCM is a high-speed memory that is tightly coupled to the processor core, providing low-latency access to critical data and code. When used effectively, TCM can significantly reduce memory access bottlenecks, allowing the processor to achieve higher performance. However, the effectiveness of TCM depends on how well the compiler can allocate frequently accessed data and code to TCM, as well as how well it can optimize the memory access patterns to minimize latency.
Compiler Optimization Strategies and TCM Allocation
The discrepancy in CoreMark scores between GCC and IAR can be attributed to several factors, including differences in compiler optimization strategies, TCM allocation, and the handling of pipeline stalls. The IAR compiler appears to be more effective at optimizing the Cortex-R52’s pipeline, reducing stalls, and maximizing instruction throughput. Additionally, the IAR compiler may be better at allocating critical code and data to TCM, reducing memory access latency and improving overall performance.
One of the key differences between GCC and IAR is the way they handle instruction scheduling and pipeline optimization. The Cortex-R52’s dual-issue superscalar architecture allows it to execute two instructions per cycle, but only if the instructions are independent and do not cause pipeline stalls. The IAR compiler may be more effective at reordering instructions to maximize parallelism and minimize stalls, resulting in higher CoreMark scores. In contrast, the GCC compiler may be less aggressive in its optimization strategies, leading to more pipeline stalls and lower performance.
Another important factor is the allocation of code and data to TCM. The Cortex-R52 supports both instruction TCM (ITCM) and data TCM (DTCM), which can be used to store critical code and data for low-latency access. The IAR compiler may be better at identifying which code and data should be placed in TCM, and at optimizing the memory access patterns to take full advantage of TCM. In contrast, the GCC compiler may not be as effective at TCM allocation, leading to more frequent accesses to slower external memory and lower CoreMark scores.
Finally, the IAR compiler may include specific optimizations for the Cortex-R52 that are not present in GCC. These optimizations could include specialized instruction scheduling algorithms, better handling of branch prediction, and more effective use of the processor’s cache. These optimizations could contribute to the higher CoreMark scores observed with the IAR compiler.
Achieving Optimal CoreMark Performance on Cortex-R52
To achieve the advertised CoreMark performance of 4.3 CoreMark/MHz on the Cortex-R52, developers should focus on three key areas: compiler selection, TCM utilization, and code optimization. The choice of compiler is critical, as the IAR compiler has been shown to achieve higher CoreMark scores than GCC. Developers should also ensure that critical code and data are allocated to TCM, and that memory access patterns are optimized to minimize latency. Finally, developers should carefully optimize their code to take full advantage of the Cortex-R52’s dual-issue superscalar architecture, minimizing pipeline stalls and maximizing instruction throughput.
When selecting a compiler, developers should consider not only the CoreMark scores but also the specific optimizations that the compiler provides for the Cortex-R52. The IAR compiler, for example, may include specialized optimizations that are not available in GCC. Developers should also consider the ease of use and the availability of support and documentation for the compiler, as these factors can have a significant impact on development time and effort.
TCM utilization is another critical factor in achieving optimal CoreMark performance. Developers should carefully analyze their code to identify critical code and data that should be placed in TCM. This may include frequently accessed data, time-critical code, and interrupt handlers. Once the critical code and data have been identified, developers should use the compiler’s TCM allocation features to ensure that they are placed in TCM. Additionally, developers should optimize their memory access patterns to minimize latency and maximize throughput.
Finally, developers should optimize their code to take full advantage of the Cortex-R52’s dual-issue superscalar architecture. This may include reordering instructions to maximize parallelism, minimizing pipeline stalls, and using specialized instructions to improve performance. Developers should also consider using profiling tools to identify performance bottlenecks and optimize their code accordingly.
In conclusion, achieving optimal CoreMark performance on the Cortex-R52 requires careful attention to compiler selection, TCM utilization, and code optimization. By selecting the right compiler, effectively utilizing TCM, and optimizing their code, developers can achieve the advertised CoreMark performance of 4.3 CoreMark/MHz and fully leverage the capabilities of the Cortex-R52 processor.
