Time spent on CS assertion, software processing, or idle time between frames.
Calculation Results
Raw Bit Rate:–
Raw Byte Rate:–
Transfer Time (per Frame):–
Total Time (incl. Overhead):–
Effective Throughput:–
function calculateSPIDataRate() {
// Get Inputs
var freqInput = document.getElementById('spiClockFreq').value;
var freqUnit = document.getElementById('spiClockUnit').value;
var busWidth = document.getElementById('spiBusWidth').value;
var frameSize = document.getElementById('spiFrameSize').value;
var overhead = document.getElementById('spiOverhead').value;
// Validation
if (freqInput === "" || isNaN(freqInput) || freqInput <= 0) {
alert("Please enter a valid Clock Frequency.");
return;
}
if (frameSize === "" || isNaN(frameSize) || frameSize <= 0) {
frameSize = 8; // Default to byte
}
if (overhead === "" || isNaN(overhead) || overhead = 1000000000) return (bps / 1000000000).toFixed(2) + " Gbps";
if (bps >= 1000000) return (bps / 1000000).toFixed(2) + " Mbps";
if (bps >= 1000) return (bps / 1000).toFixed(2) + " kbps";
return bps.toFixed(0) + " bps";
}
function formatBytes(bps) {
var Bps = bps / 8;
if (Bps >= 1000000) return (Bps / 1000000).toFixed(2) + " MB/s";
if (Bps >= 1000) return (Bps / 1000).toFixed(2) + " kB/s";
return Bps.toFixed(0) + " B/s";
}
function formatTime(seconds) {
if (seconds === 0) return "0 ns";
if (seconds < 0.000001) return (seconds * 1000000000).toFixed(2) + " ns";
if (seconds < 0.001) return (seconds * 1000000).toFixed(2) + " µs";
if (seconds < 1) return (seconds * 1000).toFixed(2) + " ms";
return seconds.toFixed(4) + " s";
}
// Display Results
document.getElementById('resRawBitRate').innerText = formatRate(rawBitRateBps);
document.getElementById('resRawByteRate').innerText = formatBytes(rawBitRateBps);
document.getElementById('resTransferTime').innerText = formatTime(activeTimeSeconds);
document.getElementById('resTotalTime').innerText = formatTime(totalTimeSeconds);
document.getElementById('resEffectiveRate').innerText = formatRate(effectiveBitRateBps);
// Show result div
document.getElementById('spiResult').style.display = "block";
}
Understanding SPI Data Rate and Throughput
The Serial Peripheral Interface (SPI) is a synchronous serial communication interface specification used for short-distance communication, primarily in embedded systems. Calculating the data rate involves more than just knowing the clock speed; it requires understanding the bus width and the overhead inherent in the communication protocol.
How to Calculate SPI Speed
The theoretical maximum speed of an SPI bus is determined primarily by the Serial Clock (SCLK) frequency and the number of data lines used (the mode).
Theoretical Formula: Data Rate (bps) = Frequency (Hz) × Number of Data Lanes
Standard SPI: Uses 1 data line (MOSI/MISO). Data is transferred 1 bit per clock cycle. Throughput = Clock Frequency.
Dual SPI: Uses 2 data lines. Data is transferred 2 bits per clock cycle. Throughput = 2 × Clock Frequency.
While the raw data rate gives you the speed of bits moving across the wire during an active transmission, the effective throughput is often lower due to overhead.
Overhead factors include:
Chip Select (CS) Latency: The time required to pull the CS line low before transmission and high after transmission.
Software Overhead: The time the MCU takes to load the transmit buffer or read the receive buffer.
Inter-byte Delay: Some peripherals require a small delay between bytes or frames to process data.
Example Calculation
Consider a system running standard SPI at 10 MHz transferring 8-bit packets with a 2 µs delay between packets.
Raw Bit Rate: 10 MHz × 1 = 10 Mbps.
Active Transfer Time: 8 bits / 10 Mbps = 0.8 µs.
Total Time per Packet: 0.8 µs (active) + 2.0 µs (delay) = 2.8 µs.
In this scenario, despite a 10 Mbps clock, the real-world speed is less than 3 Mbps due to the delay overhead.
Common SPI Applications
SPI is widely used for connecting microcontrollers to sensors, SD cards, shift registers, and LCD displays. High-speed variants like Quad SPI are frequently used for external flash memory (XIP – Execute in Place) where high data throughput is critical for system performance.