Xilinx 的 Versal AI Core 系列器件旨在解決獨特且最困難的 AI 推理問題，方法是使用高計算效率 ASIC 級 AI 計算引擎和靈活的可編程結(jié)構(gòu)來構(gòu)建具有加速器的 AI 應(yīng)用，從而最大限度地提高任何給定工作負載的效率，同時提供低功耗和低延遲。

Versal AI Core 系列VCK190 評估套件采用VC1902器件，該器件在產(chǎn)品組合中具有最佳的 AI 性能。該套件專為需要高吞吐量 AI 推理和信號處理計算性能的設(shè)計而設(shè)計。VCK190 套件的計算能力是當(dāng)前服務(wù)器級 CPU 的 100 倍，并具有多種連接選項，是從云到邊緣的各種應(yīng)用的理想評估和原型設(shè)計平臺。

圖 1：賽靈思 Versal AI 內(nèi)核系列 VCK190 評估套件。（圖片來源：AMD， Inc）

VCK190 評估套件的主要特性

• 板載 Versal AI 核心系列設(shè)備
  • 配備 Versal ACAP XCVC1902 量產(chǎn)芯片
  • AI 和 DSP 引擎的計算性能比當(dāng)今的服務(wù)器級 CPU 高 100 倍
  • 用于快速原型設(shè)計的預(yù)構(gòu)建合作伙伴參考設(shè)計
• 用于前沿應(yīng)用開發(fā)的最新連接技術(shù)
  • 內(nèi)置 PCIe 第 4 代硬 IP，用于高性能設(shè)備接口，如 NVMe? 固態(tài)盤和主機處理器
  • 內(nèi)置 100G EMAC 硬 IP，用于高速 100G 網(wǎng)絡(luò)接口
  • DDR4 和 LPDDR4 內(nèi)存接口
• 協(xié)同優(yōu)化工具和調(diào)試方法
  • Vivado? ML， Vitis 統(tǒng)一軟件平臺， Vitis? AI， 用于 AI 推理應(yīng)用開發(fā)的 AI 引擎工具

利用賽靈思 Versal AI 內(nèi)核系列器件實現(xiàn) AI 接口加速

圖 2：賽靈思 Versal AI 內(nèi)核 VC1902 ACAP 器件框圖。（圖片來源：AMD， Inc）

Versal? AI Core 自適應(yīng)計算加速平臺 （ACAP） 是一款高度集成的多核異構(gòu)設(shè)備，可在硬件和軟件級別動態(tài)適應(yīng)各種 AI 工作負載，使其成為 AI 邊緣計算應(yīng)用或云加速器卡的理想選擇。該平臺集成了用于嵌入式計算的下一代標(biāo)量引擎、用于硬件靈活性的自適應(yīng)引擎，以及由 DSP 引擎和用于推理和信號處理的革命性 AI 引擎組成的智能引擎。其結(jié)果是一個適應(yīng)性強的加速器，其性能、延遲和能效超過了傳統(tǒng) FPGA 和 GPU 的性能、延遲和能效，適用于 AI/ML 工作負載。

Versal ACAP 平臺亮點

• 適應(yīng)性強的引擎：
  • 自定義內(nèi)存層次結(jié)構(gòu)優(yōu)化了加速器內(nèi)核的數(shù)據(jù)移動和管理
  • 預(yù)處理和后處理功能，包括神經(jīng)網(wǎng)絡(luò) RT 壓縮和圖像縮放
• 人工智能引擎 （DPU）
  • 矢量處理器的平鋪陣列，使用 XCVC1902 設(shè)備（稱為深度學(xué)習(xí)處理單元或 DPU）時，性能高達 133 INT8 TOPS
  • 非常適合神經(jīng)網(wǎng)絡(luò)，包括CNN，RNN和MLP;硬件可適應(yīng)不斷演變的算法進行優(yōu)化
• 標(biāo)量引擎
  • 四核ARM處理子系統(tǒng)，用于安全、電源和比特流管理的平臺管理控制器

VCK190 人工智能推理性能

與當(dāng)前服務(wù)器級 CPU 相比，VCK190 能夠提供超過 100 倍的計算性能。下面是基于 C32B6 DPU 內(nèi)核的 AI 引擎實現(xiàn)的性能示例，批處理 = 6。有關(guān) VCK190 上各種神經(jīng)網(wǎng)絡(luò)樣本的吞吐量性能（以幀/秒或 fps 為單位），DPU 以 1250 MHz 運行，請參閱下表。

| | No | Neural Network | Input Size | GOPS | Performance (fps) (Multiple thread) |
| ---- | -------------------------- | ------------ | ------ | ------------------------------------- |
| 1 | face_landmark | 96x72 | 0.14 | 24605.3 |
| 2 | facerec_resnet20 | 112x96 | 3.5 | 5695.3 |
| 3 | inception_v2 | 224x224 | 4 | 1845.8 |
| 4 | medical_seg_cell_tf2 | 128x128 | 5.3 | 3036.3 |
| 5 | MLPerf_resnet50_v1.5_tf | 224x224 | 8.19 | 2744.2 |
| 6 | RefineDet-Medical_EDD_tf | 320x320 | 9.8 | 1283.6 |
| 7 | tiny_yolov3_vmss | 416x416 | 5.46 | 1424.4 |
| 8 | yolov2_voc_pruned_0_77 | 448x448 | 7.8 | 1366.0 |

Table 1: Example of VCK190 AI Inference performance.

See more detail of VCK190 AI performance from Vitis AI Library User Guide (UG1354), r2.5.0 at https://docs.xilinx.com/r/en-US/ug1354-xilinx-ai-sdk/VCK190-Evaluation-Board

How Design Gateway's IP cores accelerate AI application performance?

Design Gateway's IP Cores are designed to handle Networking and Data Storage protocol without need for CPU intervention. This makes it ideal to fully offload CPU systems from complicated protocol processing and which enables them to utilize most of their computing power for AI applications including AI inference, pre and post data processing, user interface, network communication and data storage access for the best possible performance.

Figure 3: Block diagram of example an AI Application with Design Gateway's IP Cores. (Image source: Design Gateway)

Design Gateway's TCP Offload Engine IP (TOExxG-IP) performance

Processing high speed, high throughput TCP data streams over 10GbE or 25GbE by traditional CPU systems needs more than 50% of CPU time which reduces overall performance of AI applications. According to 10G TCP performance test on Xilinx's MPSoC Linux systems, CPU usage during 10GbE TCP transmission is more than 50%, TCP send and receive data transfer speed could be achieved just around 40% to 60% of 10GbE speed or 400 MB/s to 600 MB/s.

By implementing Design Gateway's TOExxG-IP Core, CPU usage for TCP transmission over 10GbE and 25GbE can be reduced to almost 0% while ethernet bandwidth utilization can be achieved close to 100%. This allows the sending and receiving of data over the TCP network directly by pure hardware logic and be fed into the Versal AI Engine with minimum CPU usage and the lowest possible latency. Figure 4 below shows the CPU usage and TCP transmission speed comparison between TOExxG-IP and MPSoC Linux systems.

Figure 4: Performance comparison of 10G/25G TCP transmission by MPSoC Linux systems and Design Gateway's TOExxG-IP Core. (Image source: Design Gateway)

Design Gateway’s TOExxG-IP for Versal devices

Figure 5: TOExxG-IP systems overview. (Image source: Design Gateway)

The TOExxG-IP core implements the TCP/IP stack (in hardwire logic) and connects with Xilinx’s EMAC Hard IP and Ethernet Subsystem module for the lower-layer hardware interface with 10G/25G/100G Ethernet speed. The user interface of the TOExxG-IP consists of a Register interface for control signals and a FIFO interface for data signals. The TOExxG-IP is designed to connect with Xilinx's Ethernet subsystem through the AXI4-ST interface. The clock frequency of the user interface depends on the Ethernet interface speed (e.g., 156.625 MHz or 322.266 MHz).

TOExxG-IP’s features

• Full TCP/IP stack implementation without need of the CPU
• Supports one session with one TOExxG-IP
• Multi-session can be implemented by using multiple TOExxG-IP instances
• Support for both Server and Client mode (Passive/Active open and close)
• Supports Jumbo frame
• Simple data interface by standard FIFO interface
• Simple control interface by single port RAM interface

FPGA resource usages on the XCVC1902-VSVA2197-2MP-ES FPGA device are shown in Table 2 below.

| | Family | Example Device | Fmax (MHz) | CLB Regs | CLB LUTs | Slice | IOB | BRAMTile^1^ | URAM | Design Tools |
| ---------------- | -------------------------- | ------------ | ---------- | ---------- | ------- | ----- | -------------- | ------ | -------------- |
| Versal AI Core | XCVC1902-VSVA2197-2MP-ES | 350 | 11340 | 10921 | 2165 | - | 51.5 | - | Vivado2021.2 |

Table 2: Example Implementation Statistics for Versal device.

More details of the TOExxG-IP are described in its datasheet which can be downloaded from Design Gateway’s website at the following links:

• TOE10G-IP Core Xilinx Datasheet
• TOE25G-IP Core Xilinx Datasheet
• TOE100G-IP Core Xilinx Datasheet

Design Gateway's NVMe Host Controller IP performance

NVMe Storage interface speed with PCIe Gen3 x4 or PCIe Gen4 x4 has data rates up to 32 Gbps and 64 Gbps. This is three to six times higher than 10GbE Ethernet speed. Processing complicated NVMe storage protocol by the CPU to achieve the highest possible disk access speed requires more CPU time than TCP protocol over 10GbE.

Design Gateway solved this problem by developing the NVMe IP core that is able to run as a standalone NVMe host controller, able to communicate with an NVMe SSD directly without the CPU. This enables a high efficiency and performance of the NVMe PCIe Gen3 and Gen4 SSD access, which simplifies the user interface and standard features for ease of usage without needing knowledge of the NVMe protocol. NVMe PCIe Gen4 SSD performance can achieve up to a 6 GB/s transfer speed with NVMe IP as shown in Figure 6.

Figure 6: Performance comparison of NVMe PCIe Gen3 and Gen4 SSD with Design Gateway's NVMe-IP Core. (Image source: Design Gateway)

Design Gateway's NVMe-IP’s for Versal devices

圖 7：NVMe-IP 系統(tǒng)概述。（圖片來源：設(shè)計網(wǎng)關(guān)）

NVMe-IP的功能

• 能夠?qū)崿F(xiàn)應(yīng)用層、事務(wù)層、數(shù)據(jù)鏈路層和物理層的某些部分，無需CPU或外部DDR存儲器即可訪問NVMe SSD
• 與賽靈思 PCIe 第 3 代和第 4 代硬 IP 配合使用
• 能夠利用BRAM和URAM作為數(shù)據(jù)緩沖區(qū)，而無需外部存儲器接口
• 支持六個命令：識別、關(guān)機、寫入、讀取、SMART 和刷新（提供可選的附加命令支持）

XCVC1902-VSVA2197-2MP-E-S FPGA 器件上的 FPGA 資源使用情況如表 2 所示。

| | 家庭 | 示例設(shè)備 | 最大頻率 （兆赫） | 負載均衡注冊 | 負載均衡 LUT | 片 | IOB | 布拉姆蒂勒^1^ | 烏蘭 | 設(shè)計工具 |
| ---------------- | -------------------------- | ------------------- | -------------- | -------------- | ------ | ----- | ---------------- | ------ | ------------ |
| Versal AI Core | XCVC1902-VSVA2197-2MP-ES | 375 | 6280 | 3948 | 1050 | - | 4 | 8 | 萬歲2022.1 |

表 3：Versal 設(shè)備的實現(xiàn)統(tǒng)計信息示例。

有關(guān) Versal 器件的 NVMe-IP 的更多詳細信息，請參見其數(shù)據(jù)表，可通過以下鏈接從 Design Gateway 的網(wǎng)站下載：

面向第四代賽靈思的 NVMe IP 核數(shù)據(jù)表

結(jié)論

TOExxG-IP 和 NVMe-IP 內(nèi)核都可以通過將 CPU 系統(tǒng)從計算和內(nèi)存密集型協(xié)議（如 TCP 和 NVMe 存儲協(xié)議）中完全卸載來幫助加速 AI 應(yīng)用程序性能，這對于實時 AI 應(yīng)用程序至關(guān)重要。這使得賽靈思的 Versal AI Core 系列器件能夠執(zhí)行 AI 推理和高性能計算應(yīng)用，而不會出現(xiàn)網(wǎng)絡(luò)和數(shù)據(jù)存儲協(xié)議處理的瓶頸或延遲。

VCK190 評估套件和 Design Gateway 的網(wǎng)絡(luò)和存儲 IP 解決方案可在 Xilinx 的 Versal AI Core 器件上以盡可能低的 FPGA 資源使用量和極高的能效在 AI 應(yīng)用中實現(xiàn)最佳性能。