9.2 Reconfigurable computing and FPGAs

Reconfigurable computing lets us tweak hardware after it's made, giving us flexibility and power efficiency. It's like having a shape-shifting computer that adapts to what we need. This is super useful for tasks that need speed and efficiency.

FPGAs are the stars of this show. They're like digital Lego sets, with blocks we can rearrange to create custom circuits. We program them using special languages, making them perfect for tasks ranging from signal processing to AI.

Reconfigurable Computing

Definition and Advantages

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• Reconfigurable computing utilizes hardware that can be reconfigured or reprogrammed post-fabrication to perform specific tasks or functions
• Offers flexibility by allowing the hardware to be adapted to the specific requirements of a given application or algorithm
• Advantages include:
  • Improved performance compared to software implementations on general-purpose processors (hardware optimization for specific tasks)
  • Energy efficiency (tailored hardware minimizes power consumption for a given application)
  • Adaptability to changing requirements or standards (hardware can be reconfigured to accommodate updates or modifications)
  • Reduced time-to-market and development costs compared to custom ASIC designs (reconfigurable hardware can be quickly modified and iterated upon)

FPGA Architecture and Components

Basic Building Blocks

• Field-Programmable Gate Arrays (FPGAs) are the most common type of reconfigurable hardware
• Consist of an array of programmable logic blocks, interconnects, and input/output (I/O) blocks
• Programmable logic blocks, also known as configurable logic blocks (CLBs), contain:
  • Look-up tables (LUTs) for implementing combinational logic functions
  • Flip-flops for sequential logic and storage elements
  • Multiplexers for selecting and routing signals
• Programmable interconnects allow the logic blocks to be connected together to form complex digital circuits (configured to create the desired routing between elements)

Specialized Components

• I/O blocks provide an interface between the FPGA and external devices (support various signaling standards and protocols)
• Modern FPGAs also include specialized components:
  • Embedded memory blocks (Block RAMs) for on-chip data storage
  • Digital Signal Processing (DSP) blocks optimized for signal processing applications (filtering, FFT, MAC operations)
  • High-speed serial transceivers for efficient communication with external devices (PCIe, Ethernet, SerDes)
  • Embedded processors (ARM cores) for software-based control and management tasks

Programming FPGAs

Hardware Description Languages (HDLs)

• FPGA development typically involves describing the desired hardware functionality using HDLs such as VHDL or Verilog
• HDLs allow designers to describe the structure and behavior of digital circuits at various levels of abstraction:
  • Gate-level descriptions (specifying individual logic gates and their connections)
  • Register-transfer level (RTL) descriptions (defining the flow of data between registers and the logical operations performed on them)
  • Algorithmic descriptions (using high-level constructs like loops and conditionals to describe the desired functionality)

High-Level Synthesis (HLS) and Development Tools

• High-Level Synthesis (HLS) tools enable the use of high-level programming languages like C, C++, or OpenCL to describe hardware functionality
  • Examples: Xilinx Vivado HLS, Intel OpenCL
  • HLS tools automatically generate HDL code from the high-level descriptions (facilitates faster development and easier integration with software components)
• FPGA vendors provide Integrated Development Environments (IDEs) that include tools for:
  • Design entry (schematic capture, HDL editors)
  • Simulation (functional and timing simulation)
  • Synthesis (converting HDL or HLS descriptions into a netlist)
  • Implementation (mapping the netlist onto the FPGA's physical resources and generating the bitstream)
  • Examples: Xilinx Vivado, Intel Quartus Prime

Applications for Reconfigurable Computing

Characteristics of Suitable Applications

• Reconfigurable computing is well-suited for applications with the following characteristics:
  • Computationally intensive tasks that can benefit from hardware acceleration
  • Algorithms with inherent parallelism that can be exploited by the FPGA's architecture
  • Applications requiring low latency and high throughput (real-time signal processing, high-frequency trading)
  • Systems with evolving requirements or standards that may necessitate hardware updates or modifications

Application Domains

• Digital Signal Processing (DSP) and image processing (radar, sonar, medical imaging)
• Cryptography and security (encryption, decryption, secure communication protocols)
• Networking and telecommunications (packet processing, network virtualization, software-defined radio)
• High-performance computing and scientific simulations (molecular dynamics, finite element analysis)
• Automotive and aerospace systems (sensor fusion, computer vision, control systems)
• Machine learning and artificial intelligence (accelerating inference and training tasks)