A Precision Converter FPGA Integration Journey

This workshop goes through the whole stack for the integration of a precision converter using an FPGA, demonstrating how to achieve maximum performance with the SPI Engine Framework.

Prerequisites

Before starting this workshop, you should have:

Basic understanding of FPGA development concepts
Familiarity with SPI protocol fundamentals
Access to Cora Z7S development board (optional for hands-on)
ADALM2000 (M2K) for testing (optional)

Learning Objectives

By the end of this workshop, you will:

Understand why traditional MCU SPI controllers limit converter performance
Learn the SPI Engine Framework architecture and components
Build a complete AD7984 precision converter system
Compare regular SPI vs. SPI Engine performance metrics
Achieve near-datasheet performance with proper FPGA integration

Introduction

Customer Journey

https://media.githubusercontent.com/media/analogdevicesinc/documentation/main/docs/learning/workshop_a_precision_converter_fpga_integration_journey/intro_customer_journey_1.png — Figure 1 Customer development journey: ADI provides reference designs that port to current development environments and evaluation kits.

Note

Tools and platforms are a customer choice. ADI maintains reference designs across multiple FPGA vendors and development boards to support diverse needs.

COS Reference Design “Donut Hole” Strategy

The strategy focuses on surrounding customer-selected processors, FPGAs, and microcontrollers with ADI components, creating a seamless integration experience.

Key Benefits:

Low Friction:: Customers experience minimal integration effort
Ecosystem Leverage:: Participation in thriving open-source communities
Design Stickiness:: Reference designs encourage continued ADI component usage
Community Support:: Access to massive user bases across platforms

Ecosystem Scale:

Linux kernel: 1.3 Billion users
GitHub: 40 Million users
Python: 100 Million users
MATLAB: 1 Million users

COS Full Stack High Level Overview

COS Full Stack HDL Designs

COS Typical Prototyping System

Supported FPGA Platforms:

Vendor	Supported Platforms
AMD/Xilinx	Zynq-7000 \| VersalAI Core \| Virtex UltraScale+ \| Versal Prime Series \| Versal Premium \| Zynq UltraScale+
Intel/Altera	Arria 10 SoC \| Stratix 10 SoC \| Cyclone 5 SoC \| Agilex 7 I-Series
Lattice	CertusPro-NX

COS IP Library

COS Frameworks - JESD204 Interface Framework

The JESD204 framework provides a complete solution for high-speed converter interfaces.

JESD204 Layer Architecture:

Physical Layer:: FPGA-specific transceivers (GTXE2, GTHE3, GTHE4, GTY4, GTY5, Arria 10, Stratix 10)
Data Link Layer:: Available under GPL 2 and commercial license
Transport Layer:: Converter-specific implementations for ADCs, DACs, and transceivers

Complete Framework Includes:

Evaluation boards with FMC connectivity
Production-ready HDL IP cores
Linux device drivers and software APIs

COS Frameworks - SPI Engine Framework

Tip

SPI Engine Powers Over 20% of ADI’s HDL Projects

The SPI Engine framework is a critical component for precision converter integration, supporting a wide range of SAR ADCs and other SPI devices.

HDL Project Distribution:

SPI Engine Framework Modules:

AXI SPI Engine (CSG):: Core SPI interface with memory-mapped control
Offload Engine (CSG):: Efficient autonomous data handling and streaming
Interconnect:: Bridges application and interface logic with arbitration
Execution Engine (CSE):: Command stream execution and physical SPI signal generation

Framework Includes:

ADC/DAC support: Extensive library of precision converter drivers
HDL components: Standard and custom IP blocks for AMD Xilinx and Intel FPGAs
Software support: Bare-metal APIs and Linux kernel driver integration

SPI Engine Architecture

Serial Peripheral Interface (SPI) - Background

SPI is a full-duplex serial communication bus designed by Motorola in the mid-1980s. It is widely used for short-distance chip-to-chip communication in embedded systems and has become a de facto industry standard despite small variations across implementations.

SPI Signal Definitions:

SCLK:: Serial Clock from master (sets transfer rate)
MOSI:: Master Output Slave Input (data from master to slave)
MISO:: Master Input Slave Output (data from slave to master)
CSN:: Chip Select N, active low (enables specific slave device)

SPI Operating Modes:

SPI supports four operating modes based on two configuration bits: CPOL (Clock Polarity) and CPHA (Clock Phase).

Mode	CPOL	CPHA	Description
Mode 0	0	0	Clock idle LOW, data sampled on RISING edge, shifted on falling edge
Mode 1	0	1	Clock idle LOW, data sampled on FALLING edge, shifted on rising edge
Mode 2	1	0	Clock idle HIGH, data sampled on FALLING edge, shifted on rising edge
Mode 3	1	1	Clock idle HIGH, data sampled on RISING edge, shifted on falling edge

SPI Mode Timing Diagrams:

Why MCU SPI Controllers Are Not Sufficient for Precision Converters

Important

Critical Limitation: MCU SPI Controllers Cannot Achieve Datasheet Performance

Traditional MCU SPI controllers introduce timing jitter and limit sampling rates, preventing precision converters from reaching their full potential.

Physical Layer Limitations:

3-wire SPI support (less common than 4-wire)
CS often serves dual purposes (chip select AND conversion trigger)
No support for additional control lines (BUSY, CNV)
Single MOSI/MISO line limitation
SCLK frequency limited to ~50MHz (higher speeds rare)
Fixed timing relationships between interface signals
No synchronization capability with external signals
No DDR (double data rate) support

Software-Driven Performance Issues:

High Latency:: Software overhead prevents fast response times
No Streaming:: Cannot support continuous high-throughput data capture
Non-Deterministic:: Time between function call and actual transfer is variable
CPU Overhead:: Processor must manage every transfer, limiting system performance

Attention

The combination of these limitations means MCU SPI controllers typically achieve only 15-20% of a converter’s datasheet performance specifications!

SPI Transfer Timing Examples

SPI Engine Framework – The Solution

Note

Open-Source, Production-Ready Framework

SPI Engine is a highly flexible and powerful open-source SPI controller framework specifically designed to overcome the limitations of traditional SPI controllers.

The framework consists of multiple submodules that communicate over well-defined interfaces, enabling high flexibility and reusability while remaining highly customizable and easily extensible.

Key Framework Features:

Multi-Vendor HDL:: Supports both AMD Xilinx and Intel FPGAs
Linux Integration:: Fully integrated into the Linux kernel SPI framework
Bare-Metal Support:: Standalone API for RTOS and bare-metal applications
Production Ready:: Extensively tested with numerous ADI converters
Open Source:: Available on GitHub with active community support

Benefits Over Traditional SPI:

Hardware-driven transfers with deterministic timing
Support for high-speed continuous streaming (>100 MSPS data rates)
Sub-microsecond latency for conversion triggers
Flexible timing control to meet any converter’s requirements
Simultaneous support for multiple SPI devices

SPI Engine Framework – HDL Architecture

The SPI Engine uses a modular architecture with three main components communicating via standardized AXI-Stream interfaces.

Component Descriptions:

Command Stream Generator (CSG)

Generates SPI command sequences. Can operate in multiple modes:

Software driven: Controlled through memory-mapped registers
Hardware driven: Triggered by external events for data offload
Periodic: Generates commands at fixed intervals
Synchronous: Responds to external trigger signals

Command Stream Executor (CSE)

Parses incoming command streams and drives the physical SPI pins.

Standard parser for common SPI protocols
Customizable for special requirements (e.g., custom SDI latching)
Handles all SPI modes and timing configurations

Command Stream Interconnect (CSI)

Arbitrates multiple command streams to a single executor.

Supports multiple CSGs sharing one physical SPI interface
Priority-based arbitration (lower port number = higher priority)
Transaction-level switching (uses SYNC instruction)

SPI Engine Framework – AXI SPI Engine IP

The AXI SPI Engine IP provides the memory-mapped interface for software control and configuration.

Key Features:

Memory-mapped access to command stream interface (fully software-controlled CSG)
Memory-mapped access to offload control for dynamic reconfiguration
Asynchronous clock domains (SPI clock independent of AXI clock)
FIFO buffers for command, SDO, and SDI data
Interrupt support for transfer completion

SPI Engine Framework – Data Offload IP

The Data Offload module enables autonomous, hardware-triggered SPI transfers without CPU intervention, critical for high-performance streaming applications.

Offload Capabilities:

Internal RAM/ROM stores command sequences and SDO data
External trigger launches predefined command stream
Received SDI data streams directly to AXI4-Stream interface
Direct DMA connection for zero-copy data transfer
Supports continuous, periodic sampling at maximum rates

Tip

The offload module is essential for achieving 1+ MSPS with precision converters, as it eliminates all software latency and CPU overhead.

SPI Engine Framework – Interconnect IP

The Interconnect enables multiple command sources to share a single physical SPI interface, useful when mixing software-controlled and hardware-offloaded transfers.

Interconnect Features:

Arbitrates multiple command streams to one executor
Transaction-level arbitration (complete SPI transfers are atomic)
SYNC instruction marks transaction boundaries
Priority-based: Lower slave port number = higher priority
No command stream fragmentation

SPI Engine Framework – Execution IP

The Execution module is the physical layer that converts command streams into actual SPI signal transitions with precise timing control.

Execution Features:

Accepts commands on the AXI-Stream control interface
Generates low-level SPI signals (SCLK, MOSI, MISO, CS)
Active signal indicates busy status during command processing
Configurable for all SPI modes (0-3)
Supports variable word lengths and transfer delays
Precise timing control for converter-specific requirements

SPI Engine Framework – Command Stream Interfaces

The framework uses four dedicated AXI-Stream interfaces for different data types:

CMD:: Command/instruction stream
SDO:: SPI write data stream (Master Output, Slave Input / MOSI)
SDI:: SPI read data stream (Master Input, Slave Output / MISO)
SYNC:: Synchronization event stream

Interface Characteristics:

Standard AXI-Stream handshaking protocol (ready, valid, data signals)
Allows independent flow control for each stream
Enables efficient pipelining and buffering
Simple, well-defined interface for custom IP integration

SPI Engine Framework – Software Support

The framework introduces comprehensive SPI offload capabilities to Linux and bare-metal systems.

Offload Concept:

Moves converter-specific operations from the application processor to dedicated hardware, dramatically improving performance and reducing CPU load.

Software Features:

Interrupt Offload:: Hardware manages conversion timing and interrupts
Data Offload:: Direct DMA transfers bypass CPU entirely
Universal API:: ADI converter drivers work with any offload-capable SPI controller
Linux Integration:: Part of standard kernel SPI framework (drivers/spi/spi-axi-spi-engine.c)
Bare-Metal Support:: Standalone API for embedded applications

Note

Once an ADI converter driver is written for SPI Engine, it can be used with any other offload-capable SPI controller with minimal changes.

Use Case: High-Performance AD7984 Integration

Application Requirements

System Performance Goals:

Important

Critical Requirements for Precision Measurement

Maximum Sample Rate:: Achieve full 1.33 MSPS with low jitter
Maximum SNR:: Reach datasheet specifications (98.5 dB)
Minimum THD:: Achieve -110 dB total harmonic distortion
Low CPU Overhead:: Minimize processor usage for sustained operation

Test Configuration Comparison:

Test Condition	Regular SPI	SPI Engine
Resolution (bits)	16	18 (full converter resolution)
Sampling Rate (KSPS)	15 (limited)	15 and 1330 (full rate)
Input Frequency (kHz)	1	1
Input Amplitude (dBFS)	-0.5	-0.5
Supply Voltage (V)	±2.5 and +5	±2.5 and +5

AD7984: High-Performance 18-bit SAR ADC

The AD7984 is an ideal choice for demonstrating SPI Engine capabilities due to its demanding timing requirements and excellent specifications.

Key Specifications:

Resolution:: 18 bits with no missing codes
Sample Rate:: 1.33 MSPS (maximum throughput)
Architecture:: Zero-latency SAR with internal reference
Input Range:: True differential ±VREF or single-ended 0 to VREF (2.9 V to 5 V)

AC Performance (at fIN = 1 kHz, VREF = 5 V):

SNR: 98.5 dB
THD: -110.5 dB
SINAD: 97.5 dB
Dynamic Range: 99.7 dB

Tip

These excellent specifications can only be achieved with proper FPGA-based timing control. MCU SPI controllers cannot maintain the required precision.

AD7984 SPI Transfer Timing Diagram

Timing Parameters for SPI Engine Configuration

The SPI Engine framework supports a wide range of precision converters. This table shows the key timing parameters needed for configuration.

Device	Resolution (bits)	Sample Rate (KSPS)	T_SPI_SCLK min (ns)	T_CONV max (ns)	T_CYC min (ns)	T_ACQ min (ns)
AD7942	14	250	18	2200	4000	1800
AD7946	14	500	15	1600	2000	400
AD7988-1	16	100	12	9500	1000	500
AD7685	16	250	15	2200	4000	1800
AD7687	16	250	10	2200	4000	1800
AD7691	16	250	15	2200	4000	1800
AD7686	16	500	15	1600	2000	400
AD7693	16	500	15	1600	2000	400
AD7988-5(B)	16	500	12	1600	2000	400
AD7988-5(C)	16	500	12	1200	2000	800
AD7980	16	1000	10	710	1000	290
AD7983	16	1333	12	500	750	250
AD7982	18	1000	12	710	1000	290
AD7984	18	1333	12	500	750	250

Note

AD7984 (highlighted) is used in this workshop due to its high sample rate (1.33 MSPS), 18-bit resolution, and demanding timing requirements that showcase SPI Engine capabilities.

HDL Design Block Diagram

HDL Framework Instantiation

The SPI Engine framework provides a TCL helper function to simplify instantiation.

TCL Function Signature:

Listing 1 SPI Engine creation function

proc spi_engine_create {{name "spi_engine"} {data_width 32} {async_spi_clk 1} {num_cs 1} {num_sdi 1} {sdi_delay 0} {echo_sclk 0}}

Instantiation Example for PulSAR ADC Family:

Listing 2 Instantiating SPI Engine for AD7984

source $ad_hdl_dir/library/spi_engine/scripts/spi_engine.tcl
set data_width 32
set async_spi_clk 1
set num_cs 1
set num_sdi 1
set sdi_delay 1
set hier_spi_engine spi_pulsar_adc
spi_engine_create $hier_spi_engine $data_width $async_spi_clk $num_cs $num_sdi $sdi_delay

Parameter Descriptions:

DATA_WIDTH:

Sets the data bus width for DMA connection and maximum SPI word length. For PulSAR ADCs with up to 18-bit transfers, use 32 bits.

ASYNC_SPI_CLK:

Selects the SPI Engine reference clock:

0: Use AXI clock (100 MHz)
1: Use external SPI_CLK for independent timing control (recommended)

NUM_CS:

Number of chip select lines (typically 1 for single converter)

NUM_SDI:

Number of SDI (MISO) lines for multi-lane interfaces

SDI_DELAY:

SDI latch delay in SPI clock cycles (1, 2, or 3). Required for high-speed designs with SCLK > 50 MHz to meet setup/hold timing.

PulSAR ADC Architecture

ADI AXI PWM GENERATOR

ad_ip_parameter pulsar_adc_trigger_gen CONFIG.PULSE_0_PERIOD 120
ad_ip_parameter pulsar_adc_trigger_gen CONFIG.PULSE_0_WIDTH 1
ad_connect spi_clk pulsar_adc_trigger_gen/ext_clk
ad_connect pulsar_adc_trigger_gen/pwm_0 $hier_spi_engine/offload/trigger

AXI CLKGEN

ad_ip_instance axi_clkgen spi_clkgen
ad_ip_parameter spi_clkgen CONFIG.CLK0_DIV 5
ad_ip_parameter spi_clkgen CONFIG.VCO_DIV 1
ad_ip_parameter spi_clkgen CONFIG.VCO_MUL 8
ad_connect $hier_spi_engine/m_spi pulsar_adc_spi
ad_connect spi_clk spi_clkgen/clk_0
ad_connect spi_clk spi_pulsar_adc/spi_clk

ADI AXI DMA CONTROLLER

ad_ip_parameter axi_pulsar_adc_dma CONFIG.DMA_TYPE_SRC 1
ad_ip_parameter axi_pulsar_adc_dma CONFIG.DMA_TYPE_DEST 0
ad_ip_parameter axi_pulsar_adc_dma CONFIG.CYCLIC 0
ad_ip_parameter axi_pulsar_adc_dma CONFIG.SYNC_TRANSFER_START 0
ad_ip_parameter axi_pulsar_adc_dma CONFIG.AXI_SLICE_SRC 0
ad_ip_parameter axi_pulsar_adc_dma CONFIG.AXI_SLICE_DEST 1
ad_ip_parameter axi_pulsar_adc_dma CONFIG.DMA_2D_TRANSFER 0
ad_ip_parameter axi_pulsar_adc_dma CONFIG.DMA_DATA_WIDTH_SRC 32
ad_ip_parameter axi_pulsar_adc_dma CONFIG.DMA_DATA_WIDTH _DEST 64
ad_connect spi_clk axi_pulsar_adc_dma/s_axis_aclk

Build and Test System

Complete Test Setup

Build Prerequisites

To build and run the complete system, you’ll need access to ADI’s open-source repositories.

Repository Setup and Build Environment

Follow these steps to set up your development environment with the necessary repositories and toolchain:

Important

Step 1: Create Workspace Directory

cd /mnt/c/
mkdir fae_workshop
cd fae_workshop/

Tip

Step 2: Clone HDL Repository and Checkout Branch

Clone the HDL repository and switch to the ad7984_demo branch:

git clone https://github.com/analogdevicesinc/hdl.git
cd hdl
git checkout ad7984_demo

This prepares the HDL project files needed for building the FPGA design.

Tip

Step 3: Download Cross-Compiler Toolchain

Download the ARM cross-compiler toolchain for building Linux kernel:

wget https://releases.linaro.org/components/toolchain/binaries/latest-7/arm-linux-gnueabi/gcc-linaro-7.5.0-2019.12-x86_64_arm-linux-gnueabi.tar.xz
tar -xvf gcc-linaro-7.5.0-2019.12-x86_64_arm-linux-gnueabi.tar.xz

Note

Step 4: Set Cross-Compiler Environment Variable

Configure the CROSS_COMPILE environment variable to point to your toolchain:

export CROSS_COMPILE=$(pwd)/gcc-linaro-7.5.0-2019.12-x86_64_arm-linux-gnueabi/bin/arm-linux-gnueabi-

Tip

Step 5: Clone ADI Linux Repository

Clone the Analog Devices Linux kernel repository with device drivers:

git clone https://github.com/analogdevicesinc/linux.git

This will create a linux directory containing the ADI Linux kernel sources with all necessary drivers.

After cloning the Linux repository, checkout to the ad7984_demo branch:

cd linux
git checkout ad7984_demo

HDL Project Build Instructions for Zynq Target

Now that you have the repositories set up, follow these guides to build the HDL project and boot image for your Zynq-7000 SoC target (Cora Z7S board):

Important

Building the HDL Project for Zynq

Follow the comprehensive guide to build the FPGA HDL design for Zynq platforms using Vivado:

📚 HDL Project Build Guide

This guide covers:

Setting up AMD Xilinx Vivado tools for Zynq
Building the FPGA bitstream for Zynq-7000
Generating hardware description files (.xsa)
Zynq-specific build commands and options

Tip

Creating the Zynq Boot Image (BOOT.BIN)

After building the HDL, create the complete Zynq boot image containing FPGA bitstream, FSBL, and U-Boot:

📚 Boot Image Build Guide

This guide covers:

Combining Zynq FSBL, bitstream, and U-Boot into BOOT.BIN
Creating bootable SD card image for Zynq
Devicetree compilation for Zynq-7000 platforms
Boot configuration for ARM processor + FPGA fabric

Note

Building Zynq Linux Kernel and Devicetree

Build the Linux kernel with ADI drivers and devicetree for Zynq-7000 platforms:

📚 Zynq Linux Build Guide

This guide covers:

Configuring the Linux kernel for Zynq with ADI device support
Building uImage (kernel) and devicetree blob (DTB)
Cross-compilation setup using the ARM toolchain
Installing kernel modules and preparing rootfs
Complete build commands for Zynq targets

System Build - ADALM2000 (M2K)

The ADALM2000 provides essential test and measurement capabilities for this workshop.

ADALM2000 Capabilities:

Two programmable power supplies: ±5V for converter biasing
Two-channel oscilloscope: USB-based, for analog signal monitoring
Arbitrary function generator: Two-channel signal source for ADC input
16-channel logic analyzer: 100 MS/s, 3.3V CMOS (1.8V or 5V tolerant) for SPI debug

System Build - Scopy Software

Scopy Virtual Instruments:

Oscilloscope:: Mixed-signal capability with protocol decoding
Signal Generator:: Functions and arbitrary waveforms
Spectrum Analyzer:: FFT analysis for SNR/THD measurement
Network Analyzer:: Frequency response characterization
Power Supply:: Adjustable voltage sources
Logic Analyzer:: With SPI protocol stack decoder
Digital Pattern Generator:: For stimulus generation
Voltmeter:: Precision DC measurements

System Build - Schematic

System Build - Cora Z7S Configuration

System Build - Preferences Configuration

System Build - ADALM2000 Configuration

System Build - Power Supply Configuration

System Build - Input Signal Generation

System Build - UART Configuration

System Build - Network Configuration

System Build - UART and Ethernet Testing

Step 1 - using Putty

Listing 3 ifconfig

~$

ifconfig

eth0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST>  mtu 1500
    inet 169.254.92.202  netmask 255.255.255.0  broadcast 10.48.65.255
    inet6 fe80::241:8f:d3d0:e43b  prefixlen 64  scopeid 0x20<link>
    ether 0e:23:90:e3:61:01  txqueuelen 1000  (Ethernet)
    RX packets 483757  bytes 81480222 (77.7 MiB)
    RX errors 0  dropped 0  overruns 0  frame 0
    TX packets 5562  bytes 775511 (757.3 KiB)
    TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0
    device interrupt 38

lo: flags=73<UP,LOOPBACK,RUNNING>  mtu 65536
    inet 127.0.0.1  netmask 255.0.0.0
    inet6 ::1  prefixlen 128  scopeid 0x10<host>
    loop  txqueuelen 1000  (Local Loopback)
    RX packets 83  bytes 10176 (9.9 KiB)
    RX errors 0  dropped 0  overruns 0  frame 0
    TX packets 83  bytes 10176 (9.9 KiB)
    TX errors 0  dropped 0 overruns 0  carrier 0  collisions 0

Step 2 - using Cygwin

Listing 4 ping 169.254.92.202

~$

ping 169.254.92.202

Pinging 169.254.92.202 with 32 bytes of data:
Reply from 169.254.92.202: bytes=32 time=2ms TTL=64
Reply from 169.254.92.202: bytes=32 time=1ms TTL=64
Reply from 169.254.92.202: bytes=32 time=1ms TTL=64
Reply from 169.254.92.202: bytes=32 time=1ms TTL=64

Ping statistics for 169.254.92.202:
  Packets: Sent = 4, Received = 4, Lost = 0 (0% loss),
Approximate round trip times in milli-seconds:
  Minimum = 1ms, Maximum = 2ms, Average = 1ms

Evaluate System

System Evaluation – regular SPI trigger configuration

Data Capture using Scopy 2.0 - Regular SPI controller

Note

Board IP Address: The Cora Z7S board IP address is 169.254.92.202 (obtained from running ifconfig command in PuTTY terminal)

Data capture using Scopy 2.0 - SPI controller

System Evaluation - Python script

System Evaluation – Python from the FPGA board

System Evaluation – Python Data Capture Results

System Evaluation – Python from a remote machine - optional

Data capture using Scopy 2.0 - SPI Engine

System Evaluation – Python from the FPGA board

System Evaluation – Python Data Capture Results

System Evaluation – Python from a remote machine - optional

System Evaluation – Performance Results Comparison

Note

SPI Engine Achieves Near-Datasheet Performance

Regular MCU SPI controllers achieve only 15% of datasheet SNR, while SPI Engine delivers 79% even at low sample rates and 100% of THD at maximum rate.

Performance Analysis:

Metric	Regular SPI	SPI Engine
SNR Achievement	15% of datasheet	79-89% of datasheet
Sample Rate	15 KSPS (1.1%)	1.33 MSPS (100%)
CPU Usage	High (100% per transfer)	Minimal (<1%)
Timing Jitter	Variable (μs range)	Deterministic (<1 ns)

Important

Key Takeaway: The SPI Engine framework enables precision converters to achieve their full datasheet specifications by providing deterministic, low-jitter timing that traditional MCU SPI controllers cannot deliver.

Audio Signal Quality Comparison

Debug Options - Logic Analyzer from Scopy

Debug Options – Integrated Logic Analyzer (ILA)

Comparison: Regular SPI vs. SPI Engine Waveforms

Conclusions

Workshop Summary

Through this hands-on workshop, we demonstrated the dramatic performance improvement achievable with FPGA-based SPI Engine compared to traditional MCU SPI controllers.

Key Findings:

MCU SPI Limitations: Traditional MCU controllers are suitable only for converters with sampling rates up to ~100 KSPS and can achieve only 15-20% of a converter’s datasheet performance.
FPGA Requirement for Maximum Performance: Achieving full datasheet specifications (sampling rate, SNR, THD) requires FPGA-based timing control with deterministic, low-jitter operation.
SPI Engine Framework: This highly flexible, open-source SPI controller framework successfully interfaces with a wide range of precision converters, providing:
- Hardware-driven, deterministic timing
- Support for 1+ MSPS continuous streaming
- Near-datasheet AC performance (>79% SNR achievement)
- Minimal CPU overhead (<1%)
Production-Ready Solution Stack: The complete COS (Customer Obsession through Software) open-source ecosystem provides HDL, Linux drivers, and tools for rapid development and deployment.

Performance Achieved:

1.33 MSPS continuous sampling (vs. 15 KSPS with MCU SPI)
77.7 dB SNR at full rate (vs. 14.8 dB with MCU SPI)
-110 dB THD matching datasheet (vs. -45.6 dB with MCU SPI)

Thank You!

Related Workshops and Presentations:

My customer uses an FPGA in his product. Now what?
ADALM2000 in real life applications
Just enough Software and HDL for High-Speed designs
Hardware and Software Tools for Precision Wideband Instrumentation

Questions? Community Support:

EngineerZone

Hardware Reference: