XC7K420T-2FF1156I_XC7Z030-3FFG676C Introduction

On the other hand, AMD and Xilinx have been working closely together for a long time. A series of storage system-oriented IPs such as NVMe HA, NVMe TC and Embedded RDMA previously provided for AMD EPYC (Xiaolong) data center processors can help AMD build low latency The high-efficiency data path, thus realizing the efficient storage acceleration function of FPGA. In fact, a similar plot was staged as early as 2015, when Intel (Intel) acquired FPGA manufacturer Altera for $16.7 billion, and Altera also followed the trend for Intel's follow-up "CPU+xPU (GPU+FPGA+ASIC+ eASIC)” strategy provides the most solid foundation.

It was the largest M&A transaction in the United States at the time and the largest acquisition in ADI's history. In July 2020, U.S. chip giant Analog Devices Inc (ADI) announced that it plans to acquire rival Maxim Integrated Products for $20.9 billion in an all-stock deal to boost its presence in companies including telecommunications. capabilities in multiple industries.

XC7K420T-2FF1156I_XC7Z030-3FFG676C

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It is a preconfigured, ready-to-run image for executing Dijkstra's shortest path search algorithm on Amazon's FGPA-accelerated F1. GraphSim is a graph-based ArtSim SSSP algorithm. The resulting archive conforms to the RFC 1952 GZIP file format specification. Go language to FPGA platform builds custom, reprogrammable, low-latency accelerators using software-defined chips. The GZIP accelerator provides hardware-accelerated gzip compression up to 25 times faster than CPU compression.

This means that in addition to the memory local to the tile, the AI engine can also access the local memory of 3 adjacent tiles (unless the tiles are at the edge of the array). Each AI Engine tile contains: 1 tile interconnect block for processing AXI4-Stream and memory mapped AXI4 input/output 1 memory block containing 32 KB of data memory subdivided into 8 memory banks, 1 memory interface, DMA and various locks. 1 AI Engine The AI Engine can access up to 4 memory modules (as 1 contiguous memory block) in all 4 directions.

This makes them highly valuable in rapid prototyping and rapidly emerging technologies. In the FPGA space, Intel is another major player, having established itself in the space with its 2015 acquisition of Altera. Xilinx, mostly known as microchips called Field Programmable Gate Arrays (FPGAs), is the leading company in this field. Unlike standard chips, they can be reprogrammed after production.

Note, however, that multiple cores can run on the same AI engine tile and share processing time. These functions are dedicated to the AI engine's vector processor, allowing you to unleash huge processing power from the AI engine. A scalar processor will handle most of the code. Xilinx will provide pre-built kernels (included in the library) for users to use in their custom graphs. Any C/C++ code can be used to program the AI engine. A kernel is used to describe a specific computing process. If your goal is to design a high-performance core, you should consider a vector processor, which uses specialized functions called intrinsics. Each core will run on a single AI engine tile.

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The introduction of acap will help salespeople compete with higher-level competitors in new markets. Obviously, this is for Intel and Nvidia. Flexibility is one of the core selling points of acap. Since larger competitor altera has fallen into Intel's pocket in 2015, new competitors in sales have become Intel, nvida, and others. Especially in the era of artificial intelligence, Xilinx also hopes to use this advantage to achieve the inheritance of Intel and Invida. This equates to a successful promotion of sales, which will compete on a higher level with the likes of Intel and Nvidia. In the face of competitors such as Intel and Nvidia, we should focus on the core competitiveness of sales, that is, the hardware level can be very flexible and adaptable according to different workloads and efforts, rather than competing with them in the traditional field.

In addition, Xilinx has released the world's first FPGA-based Open Compute Accelerator Module (OAM) proof-of-concept board. Based on Xilinx UltraScale+™ VU37P FPGA and equipped with 8GB HBM memory, the mezzanine card complies with the Open Accelerator Infrastructure (OAI) specification and can support seven 25Gbps x8 links, providing a rich inter-module system topology for distributed acceleration.