Working with Alveo Accelerator Cards - 2023.2 English

Vitis Unified Software Platform Documentation: Application Acceleration Development (UG1393)

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2023.2 English

What is an FPGA

An FPGA (field-programmable gate array) is an integrated circuit that uses an array of interconnected programmable logic elements to implement any type of digital function as a physical circuit. Because the elements and the routing resources that connect them are configured after power-up, the FPGA can be repeatedly programmed to implement any set of functions required. By creating multiple copies of these functions, FPGAs are particularly well suited at implementing functions in parallel, making them extraordinarily good at serving as hardware accelerators for applications that contain high levels of parallelism. FPGAs come in different sizes with different quantities of programmable logic resources. Larger devices contain more resources, allowing designers to implement more parallel circuits, leading to higher levels of acceleration. The variety of devices provides designers with multiple cost/performance trade-offs.

Unlike GPUs, which contain processing cores that must fetch and execute instructions, FPGAs have a flexible architecture that maps code to physical logic circuitry. Like GPUs, however, it will be necessary for you to understand some of the basics of how this is done to architect your code for best results.

Alveo Block Diagram and Data Movement between Host and FPGA

Using FPGAs at its core, AMD has developed the Alveo family of PCIe Data Center accelerator cards. Each Alveo card combines three essential things: a powerful FPGA for acceleration, high-bandwidth device memory banks, and connectivity to a host server via a high-bandwidth PCIe Gen3x16 link. A number of different cards are available to provide designers with a choice of features and quantity of programmable resources. Below is the block diagram for the Alveo U250.

Although FPGAs are essentially blank devices that get configured at power-up, all Alveo cards are shipped with target platforms that provide the firmware to configure the accelerator card for specific uses. The platform must be installed with Xilinx Runtime (XRT); flashed into the device during installation, or when changing the configuration of the accelerator card.

On the AMD device, the platform consists of two physical FPGA partitions: Shell and User. Shell partition is a static region and provides basic infrastructure for the platform like PCIe connectivity, board management, sensors, clocking, and reset. User partition is a dynamic region that contains user compiled binary called .xclbin which is loaded by XRT during execution. RTL kernels are the custom logic created by the developer and programmed into the dynamic region. In this document, kernels refer to the functions that the designer is implementing into the dynamic region of the Alveo accelerator card.

Figure 1. Alveo Block Diagram

The PCIe interface is used for communication between the host and accelerator card, and to transfer data from the host into the Alveo card's device memory. This device memory serves as a Global memory, accessible by both host and hardware accelerators. The device memory included on the Alveo platform are PLRAM (small size but fast access with the lowest latency), HBM (moderate size and access speed with some latency), and DDR (large size but slow access with high latency). Depending upon the Alveo card, you may have DDR or HBM, or even both.

The block diagram shown above is of U250 and has 4 banks of DDR, each with 16GB of memory. The FPGA on the Alveo card is further subdivided into multiple super logic regions (SLRs), which aid in the architecture of very high-performance designs. But this is a slightly more advanced topic that will remain largely unnoticed as you take your first steps into Alveo development.

To further improve performance, and minimize access to DDR memory, FPGAs have large quantities of small, internal RAM blocks. These are completely configurable by the compiler to ensure that buffering can be created between tasks to enable pipeline-style computation. This effectively eliminates the need for caches and is one of the key strengths of FPGAs.

There are many more details you could learn about the FPGA architecture and Alveo cards, but this is sufficient for introductory purposes. From the perspective of designing an FPGA-based acceleration architecture, the important points to remember are:

  • Moving data across PCIe is expensive, even at Gen3x16, latency is high. For larger data transfers, bandwidth can easily become a system bottleneck.
  • Bandwidth and latency between the DDR4 and the FPGA are significantly better than over PCIe, but touching external memory is still expensive in terms of overall system performance.