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FPGAs embrace data centre co-processing role

Part 1: Xilinx's SDAccel development tool

The PCIe accelerator card has a power budget of 25W. Hyper data centres can host hundreds of thousands of servers whereas other industries with more specialist computation requirements use far fewers servers. As such, they can afford a higher power budget per card. Source: Xilinx

Xilinx has developed a software-design environment that simplifies the use of an FPGA as a co-processor alongside the server's x86 instruction set microprocessor.

Dubbed SDAccel, the development environment enables a software engineer to write applications using OpenCL, C or the C++ programming language running on servers in the data centre.   

Applications can be developed to run on the server's FPGA-based acceleration card without requiring design input from a hardware designer. Until now, a hardware engineer has been needed to convert the code into the RTL hardware description language that is mapped onto the FPGA's logic gates using synthesis tools.

"[Now with SDAccel] you suffer no degradation in [processing] performance/ Watt compared to hand-crafted RTL on an FPGA," says Giles Peckham, regional americas and EMEA marketing director at Xilinx. "And you move the entire design environment into the software domain; you don't need a hardware designer to create it."   


Data centre acceleration

The data centre is the first application targeted for SDAccel along with the accompanying FPGA accelerator cards developed by Xilinx's three hardware partners: Alpha Data, Convey and Pico Computing.

The FPGA cards connect to the server's host processor via the PCI Express (PCIe) interface are not just being aimed at leading internet content providers but also institutions and industries that have custom computational needs. These include oil and gas, financial services, medical and defence companies.  

PCIe cards have a power budget of 25W, says Xilinx. The card's power can be extended by adding power cables but considering that hyper data centres can have hundreds of thousands of servers, every extra Watt consumed comes at a cost.


Microsoft has reported that a production pilot it set up that had 1,632 servers using PCIe-based FPGA cards, achieved a doubling of throughput, a 29 percent lower latency, and a 30 percent cost reduction compared to servers without accelerator cards


In contrast, institutions and industries use far fewer servers in their data centres. "They can stomach the higher power consumption, from a cost perspective and in terms of dissipating the heat, up to a point," says Peckham. Their accelerator cards may consume up to 100W. "But both have this limitation because of the power ceiling," he says.     

China’s largest search-engine specialist, Baidu, uses neural-network processing to solve problems in speech recognition, image search, and natural language processing, according to The Linley Group senior analyst, Loring Wirbel.

Baidu has developed a 400 Gigaflop software-defined accelerator board that uses a Xilinx Kintex-7 FPGA that plugs into any 1U or 2U high server using PCIe. Baidu says that the FPGA board achieves four times higher performance than graphics processing units (GPUs) and nine times higher performance than CPUs, while consuming between 10-20W.

Microsoft has reported that a production pilot it set up that had 1,632 servers using PCIe-based FPGA cards, achieved a doubling of throughput, a 29 percent lower latency, and a 30 percent cost reduction compared to servers without accelerator cards.

"The FPGA can implement highly parallel applications with the exact hardware required," says Peckham. Since the dynamic power consumed by the FPGA depends on clock frequency and the amount of logic used, the overall power consumption is lower than a CPU or GPU. That is because the FPGA's clock frequency may be 100MHz compared to a CPU's or GPU's 1 GHz, and the FPGA implements algorithms in parallel using hardware tailored to the task.


FPGA processing performance/ W for data centre acceleration tasks compared to GPUs and CPUs. Note the FPGA's performance/W advantage increases with the number of software threads. Source: Xilinx



To develop a design environment that a software developer alone can use, Xilinx has to make SDAccel aware of the FPGA card's hardware, using what is known as a board support package. "There needs to be an understanding of the memory and communications available to the FPGA processor," says Peckham. "The processor then knows all the hardware around it."

Xilinx claims SDAccel is the industry's first architecturally optimising compiler for FPGAs. "It is as good as hand-coding [RTL]," says Peckham. The tool also delivers a CPU-/ GPU-like design environment. "It is also the first tool that enables designs to have multiple operations at different times on the same FPGA," he says. "You can reconfigure the accelerator card in runtime without powering down the rest of the chip."

SDAccel and the FPGA cards are available, and the tool is with several customers. "We have proven the tool, debugged it, created a GUI as opposed to a command line interface, and have three FPGA boards being sold by our partners," says Peckham. "More partners and more boards will be available in 2015."

Peckham says the simplified design environment appeals to companies not addressing the data centre. "One company in Israel uses a lot of Virtex-6 FPGAs to accelerate functions that start in C code," he says. "They are using FPGAs but the whole design process is drawn-out; they were very happy to learn that [with SDAccel] they don't have to hand-code RTL to program them."    

Xilinx is working to extend OpenCL for computing tasks beyond the data centre. "It is still a CPU-PCIe-to-co-processor architecture but for wider applications," says Peckham.


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