📊 Cortex-M DSP Performance Benchmark Suite REAL-TIME ANALYSIS
⚙️ Processor Configuration
216 MHz
🎯 DSP Feature Set
✅ Single Precision FPU
✅ DSP SIMD Extensions
✅ Hardware Divide
✅ Saturated Arithmetic
❌ Double Precision FPU
❌ Vector Extensions
📊 Performance Metrics
1420 DMIPS
CoreMark Score
360
Per MHz: 1.67
DSP Performance
92%
SIMD Utilization
FPU Efficiency
88%
Vectorization Rate
Memory Bandwidth
2.1 GB/s
AXI Bus Utilization
⚡ Benchmark Tasks Performance
FFT 1024-point
45.2 µs
FIR Filter (256 taps)
12.8 µs
Matrix Multiply 4x4
3.4 µs
PID Control Loop
1.2 µs
vs M4
+42%
DSP Performance
vs M3
+310%
FPU Operations
vs M0+
+850%
Overall Perf
Power Efficiency
1.8 DMIPS/mW
Energy Efficient
🔊 Real-Time Signal Processing Laboratory VISUAL DSP
🎛️ Signal Generator
1 kHz
1.0 V
🌊 Noise Parameters
Noise Level:
SNR:
20.0 dB
⚡ DSP Operations
📈 Signal Visualization
Samples: 1024 | Rate: 48 kHz
📊 Frequency Domain
⚡ DSP Performance Metrics
FFT 1024-point:
45.2 µs
FIR 256-tap:
12.8 µs
IIR Biquad:
3.4 µs
Convolution:
28.7 µs
Auto-correlation:
15.3 µs
💻 Generated DSP Code
// ARM CMSIS-DSP FFT Implementation
#include "arm_math.h"
#define FFT_SIZE 1024
float32_t fftInput[FFT_SIZE * 2];
float32_t fftOutput[FFT_SIZE];
arm_rfft_fast_instance_f32 fftInstance;
void init_fft() {
arm_rfft_fast_init_f32(&fftInstance, FFT_SIZE);
}
void process_signal() {
// Apply window function
arm_hanning_f32(fftInput, FFT_SIZE);
// Perform FFT
arm_rfft_fast_f32(&fftInstance, fftInput, fftOutput, 0);
// Compute magnitude
arm_cmplx_mag_f32(fftOutput, fftInput, FFT_SIZE/2);
}
🌀 Digital Filter Designer
1000 Hz
Sampling: 48 kHz
Passband Ripple
0.1 dB
Stopband Atten.
-40 dB
Phase Delay
12 samples
Group Delay
8 samples
🎛️ Advanced Control System Designer REAL-TIME CONTROL
⚙️ System Configuration
🎚️ PID Parameters
Kp:
2.5
Ki:
0.5
Kd:
0.1
📐 System Model
G(s) =
25
s² + 4s + 25
s² + 4s + 25
🎯 Performance Targets
Rise Time:
≤ 100 ms
Overshoot:
≤ 5%
Settling Time:
≤ 200 ms
Steady-State Error:
≤ 1%
📈 System Response
Rise Time
85 ms
✅
Overshoot
3.2%
✅
Settling Time
180 ms
✅
SS Error
0.8%
✅
💻 Control System Code
// ARM CMSIS-DSP PID Controller
#include "arm_math.h"
typedef struct {
float32_t Kp, Ki, Kd;
float32_t integral;
float32_t prev_error;
float32_t dt;
} PID_Controller;
void PID_Init(PID_Controller* pid, float32_t Kp, float32_t Ki, float32_t Kd, float32_t dt) {
pid->Kp = Kp;
pid->Ki = Ki;
pid->Kd = Kd;
pid->integral = 0.0f;
pid->prev_error = 0.0f;
pid->dt = dt;
}
float32_t PID_Update(PID_Controller* pid, float32_t setpoint, float32_t measurement) {
float32_t error = setpoint - measurement;
// Proportional term
float32_t P = pid->Kp * error;
// Integral term with anti-windup
pid->integral += error * pid->dt;
float32_t I = pid->Ki * pid->integral;
// Derivative term
float32_t derivative = (error - pid->prev_error) / pid->dt;
float32_t D = pid->Kd * derivative;
pid->prev_error = error;
// Output saturation
float32_t output = P + I + D;
return arm_sat_f32(output, -10.0f, 10.0f);
}
⚙️ Motor Control Simulation
Motor Type:
Speed Setpoint:
3000 RPM
Load Torque:
25 N·m
Field-Oriented Control:
ACTIVE
Space Vector PWM:
ACTIVE
Encoder Resolution:
4096 PPR
Phase Currents
Speed Response
Current THD
3.2%
Torque Ripple
±2.5%
Efficiency
94.8%
🧠 Neural Edge Processing (Coming Soon)
TensorFlow Lite Micro • CMSIS-NN • Neural Network Inference • Edge AI Processing • Model Optimization
CMSIS-DSP
SIMD/NEON
Control Systems
Real-Time DSP
© 2024 Arm Cortex-M DSP Performance Suite | Optimized for M4/M7/M55 with DSP and FPU
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