Xilinx U200 Data Center Accelerator Card

The Xilinx Alveo U200 is a PCIe-based data center accelerator card featuring a 3-die Virtex UltraScale+ FPGA. Beethoven provides support for building and deploying accelerators on U200 boards.

Platform Status

U200 support is available in the Beethoven codebase. Build flows and deployment scripts are platform-specific and may require customization for your environment.

Hardware Specifications

Component	Specification
FPGA	Xilinx Virtex UltraScale+
Dies/SLRs	3 (SLR0, SLR1, SLR2)
Memory	16GB DDR4 (discrete)
Interface	PCIe Gen3 x16
Clock Rate	300 MHz (default)
Memory Bandwidth	512-bit AXI4 interface (64-byte beats)

Platform Configuration

The U200 platform is configured with the following characteristics:

U200Platform configuration

class U200Platform(implicit p: Parameters) extends Platform {
  override val platformType = FPGA

  // Memory Configuration
  override val hasDiscreteMemory = true
  override val physicalMemoryBytes = 16L * 1024 * 1024 * 1024  // 16GB
  override val memoryNChannels = 1
  override val memoryControllerBeatBytes = 64  // 512-bit interface

  // Clock Configuration
  override val clockRateMHz = 300

  // Multi-Die Topology
  override val physicalDevices = List(
    DeviceConfig(0, "pblock_SLR0"),
    DeviceConfig(1, "pblock_SLR1"),
    DeviceConfig(2, "pblock_SLR2")
  )

  override val physicalConnectivity = List((0,1), (1,2))

  // Front Bus (Host Interface)
  override val frontBusBeatBytes = 4  // 32-bit AXI-Lite
}

Multi-Die Floorplanning

The U200's 3-die FPGA requires careful floorplanning for timing closure. Use Beethoven's floorplanning infrastructure to place modules across SLRs:

U200 multi-SLR accelerator

import beethoven._
import beethoven.Floorplanning._
import chipsalliance.rocketchip.config.Parameters

class U200Accelerator()(implicit p: Parameters) extends AcceleratorCore {
  // SLR0: Host interface
  val cmdInterface = BeethovenIO(
    new AccelCommand("process") {
      val input_addr = Address()
      val output_addr = Address()
      val length = UInt(32.W)
    },
    EmptyAccelResponse()
  )

  // SLR1: Memory controllers
  DeviceContext.withDevice(1) {
    val reader = getReaderModule("input_data")
    val writer = getWriterModule("output_data")
  }

  // SLR2: Compute array
  DeviceContext.withDevice(2) {
    val compute = LazyModuleWithFloorplan(
      new ComputeArray,
      2,
      "compute_array"
    )
  }
}

See the Floorplanning Guide for detailed multi-die optimization strategies.

Building Your Accelerator

Configuration

Create a build configuration targeting the U200 platform:

U200 build configuration

import beethoven._
import beethoven.Platforms._

object MyU200Build extends BeethovenBuild(
  new MyAcceleratorConfig,
  buildMode = BuildMode.Synthesis,
  platform = new U200Platform
)

Running the Build

cd Beethoven-Hardware
export BEETHOVEN_PATH=`pwd`/../my-beethoven-output
sbt run
# Select MyU200Build from the menu

This generates:

• Verilog RTL in $BEETHOVEN_PATH/build/hw/
• C++ bindings in $BEETHOVEN_PATH/build/beethoven_hardware.{h,cc}
• Constraint files in $BEETHOVEN_PATH/build/user_constraints.xdc

Synthesis with Vivado

The U200 build does not include a pre-packaged shell like AWS F2. You'll need to integrate the generated Verilog with Xilinx's U200 base design:

Vivado synthesis flow

# Create project
create_project u200_accel ./u200_project -part xcu200-fsgd2104-2-e

# Add Beethoven-generated RTL
add_files $env(BEETHOVEN_PATH)/build/hw/*.v

# Add base U200 design files
# (Platform-specific - depends on your U200 development kit)

# Add constraints
add_files -fileset constrs_1 $env(BEETHOVEN_PATH)/build/user_constraints.xdc

# Run synthesis and implementation
launch_runs synth_1
wait_on_run synth_1
launch_runs impl_1 -to_step write_bitstream
wait_on_run impl_1

Custom Integration Required

Unlike AWS F2 with its pre-built shell, U200 builds require integration with Xilinx's base design or a custom shell. Consult your U200 development kit documentation for shell integration.

Memory Interface

The U200 platform provides a single 16GB DDR4 channel with 512-bit width:

Memory channel configuration

memoryChannelConfig = List(
  ReadChannelConfig("input_data", dataBytes = 64),    // 512-bit reads
  WriteChannelConfig("output_data", dataBytes = 64)   // 512-bit writes
)

Maximum theoretical bandwidth: 300 MHz × 64 bytes = 19.2 GB/s

Memory Performance

Use wide memory interfaces (64 bytes) to maximize bandwidth utilization. Narrower interfaces (4, 8 bytes) will underutilize the memory controller.

Deployment

Bitstream Loading

Load your bitstream using Vivado Hardware Manager or Xilinx's runtime tools:

# Using Vivado Hardware Manager
vivado -mode tcl
open_hw_manager
connect_hw_server
open_hw_target
set_property PROGRAM.FILE {path/to/bitstream.bit} [get_hw_devices]
program_hw_devices [get_hw_devices]

Runtime Setup

Build the Beethoven Runtime for the U200 (discrete FPGA) platform:

cd Beethoven-Runtime
mkdir build && cd build
cmake .. -DCMAKE_BUILD_TYPE=Release -DTARGET=fpga -DBACKEND=U200
make -j
sudo ./BeethovenRuntime

Backend Support

U200 backend support may require platform-specific drivers and runtime modifications. Consult your U200 development kit documentation for PCIe driver setup.

Testbench Compilation

Your testbench compiles identically to other platforms:

CMakeLists.txt

cmake_minimum_required(VERSION 3.30)
project(u200_test)

find_package(beethoven REQUIRED)
set(CMAKE_CXX_STANDARD 17)

beethoven_build(u200_test SOURCES test.cpp)

mkdir build && cd build
cmake ..
make -j
sudo ./u200_test

Performance Optimization

Clock Frequency

The default 300 MHz clock may not meet timing for complex designs. Try:

1. Reduce clock: Change clockRateMHz in U200Platform to 250 MHz or 200 MHz
2. Add pipelining: Use RegNext() on critical paths
3. Optimize floorplanning: Place related modules on the same SLR

Memory Bandwidth

Maximize DDR4 utilization:

• Use burst transfers (large len values in reader/writer requests)
• Overlap computation with memory access
• Prefer sequential access patterns over random access

Resource Utilization

Check per-SLR utilization in Vivado:

report_utilization -hierarchical

Balance resource usage across SLRs using floorplanning constraints.

Comparison with AWS F2

Feature	U200	AWS F2
FPGA	VU+ (3 SLRs)	VU9P (3 SLRs)
Memory	16GB DDR4	16GB DDR4
Clock	300 MHz	250 MHz
Interface	512-bit	512-bit
Shell Integration	Manual	Automated
Deployment	On-premises	Cloud
Cost	Hardware purchase	Per-hour rental

When to use U200:

• On-premises deployment
• Own hardware infrastructure
• Sensitive data that can't go to cloud

When to use AWS F2:

• Cloud-native workflows
• Don't want to manage hardware
• Automated build flow with AFI generation

Troubleshooting

Timing Failures

If implementation fails timing:

1. Check critical path in timing report
2. Identify SLR crossings (often bottlenecks on multi-die FPGAs)
3. Add pipeline stages or reduce clock frequency
4. Review Floorplanning Guide for optimization

Resource Exhaustion

If synthesis fails with resource errors:

1. Check per-SLR utilization in Vivado
2. Move modules to less-utilized SLRs using DeviceContext.withDevice()
3. Reduce design size (fewer cores, smaller scratchpads)

Memory Interface Issues

If memory accesses fail:

1. Verify alignment (addresses must align to 64 bytes)
2. Check shell integration (memory interface wiring)
3. Test with simulation first to isolate hardware from FPGA board issues

See Also

• AWS F2 Platform - Similar 3-die platform with automated flow
• Floorplanning Guide - Multi-die optimization
• Custom Platform - Creating platform definitions
• Memory Interfaces - Memory channel configuration