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Inspur and Altera Launch Speech Recognition FPGA Solution with OpenCL

AUSTIN, Texas, Nov. 17, 2015 – The leading server vendor Inspur Group and the FPGA chipmaker Altera today launched a speech recognition acceleration solution based on Altera's Arria® 10 FPGAs and DNN algorithm from iFLYTEK, an intelligent speech technology provider in China, at SC15 conference in Austin, Texas. The launch results in Inspur becoming a HPC systems vendor with HPC heterogeneous computing application capabilities in GPU, MIC and FPGA.

The deep learning speech recognition acceleration solution leverages an Altera Arria 10 FPGA, iFLYTEK's deep neural network (DNN) recognition algorithms and Inspur's FPGA-based DNN parallel design, migration and optimization with OpenCL. The solution has a hardware platform in CPU+Arria 10 FPGA heterogeneous architecture and software in a high-level programming model in OpenCL to enable migration from CPU to FPGAs.

"Software algorithms for deep learning models need be fine-tuned and optimized continuously. Server accelerators with fixed functionalities will have increasingly low efficiency over time and waste space and electricity," said Yu Zhenhua, director of technology, iFLYTEK Co., Ltd. "In contrast, FPGAs are flexible, customizable and power-efficient. This is also an important reason that iFLYTEK decided to migrate DNN algorithms to a FPGA platform."

Field-Programmable Gate Arrays (FPGA), which have the characteristics of both an application-specific integrated circuit (ASIC) and a general chip, have the ability to do data parallel and task parallel computing simultaneously, which allows them to be more efficient in dealing with specific applications. FPGAs are currently used in logic control, signal processing and image processing and recently in online recognition systems.

"Inspur's Arria 10 FPGA-based deep learning speech recognition solution further demonstrates the performance-per Watt advantages that FPGA accelerators provide," said David Gamba, general manager of the computer & storage business unit at Altera. "This success in solution development will become an important reference for FPGAs in the deep learning field."

Meanwhile, Inspur is also expanding its software cooperation on the speech recognition system, designing OpenCL programming frameworks combined with iFLYTEK's applications, to increase the efficiency of application programming. With these efforts, Inspur can enable the migration of more applications to FPGA-based platforms and foster an FPGA ecosystem, which includes FPGA software, hardware and an applied algorithms library.

When speaking about further cooperation, Hu Leijun, vice president of Inspur, said that Inspur is committed to providing clients with computing solutions that best suit their needs. Given FPGA-based solutions great advantages in terms of performance per watt, Inspur will expand its software cooperation with IFLYTEK and Altera on FPGA-based deep learning online speech recognition applications. Moreover, Inspur will develop an FPGA-based system solutions, covering full cabinet computing, Internet and storage solutions, with the aim of making these solutions available for applications and clients in other fields.

In the future, a CPU+FPGA solution will probably be the new heterogeneous computing model for HPC, more and more HPC applications, data center applications and Internet deep learning applications will use CPU+FPGA solution.

The solution revealed include:

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