ZTE Wireless Institute Achieves Performance Breakthrough for Deep Learning with Intel FPGAs
January 24, 2017 -- Intel and ZTE, a leading technology telecommunications equipment and systems company, have worked together to reach a new benchmark in deep learning and convolutional neural networks (CNN). The technology is what many companies in Internet search and artificial intelligence are trying to advance, and includes picture search and matching, as one example.
“Perception, such as recognizing a face in an image, is one of the essential goals of the ZTE 5G System,” said Duan Xiangyang, vice president of ZTE Wireless Institute. “Deep learning technology is very important as it can enable such perception in mobile edge computing systems, thus making ZTE’s 5G System smarter.”
The test took place in Nanjing City, China, where ZTE’s engineers used Intel’s midrange Arria® 10 FPGA for a cloud inferencing application using a CNN algorithm.
ZTE has achieved a new record – beyond a thousand images per second in facial recognition – with what is known as “theoretical high accuracy” achieved for its custom topology. Intel’s Arria 10 FPGA accelerated the raw design performance more than 10 times while maintaining the accuracy.
The Arria 10 FPGA provides up to 1.5 teraflops (TFLOPs) single precision floating-point processing performance, 1.15 million logic elements and more than a terabit-per-second high-speed connectivity.
Such deep learning designs can be seamlessly migrated from the Arria 10 FPGA family to the high-end Intel Stratix® 10 FPGA family, and users can expect up to nine times performance boost.
Besides the impressive increase in performance, the team at ZTE Wireless Institute sped design time with the use of the OpenCL programming language.
“With the Intel reference design, and using the Intel SDK for OpenCL to program the FPGA, our development time was greatly shortened,” said Xiong Tiankui, chief engineer at ZTE Wireless Institute. “We are pleased with the benchmark achieved and thank the Intel Programmable Solutions Group for supporting our project.”
Resources:
Configuration:
The benchmark was achieved on a server holding 4S Intel Xeon E5-2670v3 processors running at 2.30GHz, 128GB DDR4; Intel PSG Arria 10 FPGA Development Kit with one 10AGX115 FPGA, 4GB DDR4 SODIMM, Intel Quartus Prime and OpenCL SDK v16.1.
|
Intel FPGA Hot IP
Related News
- Microsoft Outlines Hardware Architecture for Deep Learning on Intel FPGAs
- SK Telecom Deploys Xilinx FPGAs for AI Acceleration, Achieves 5X Performance/16X Performance-per-watt over GPUs
- Edgeware Video-on-Demand Server Achieves Breakthrough Performance With Altera FPGAs
- Nextera-Adeas ST 2110 IP cores are now available on Intel FPGAs
- Intel Launches Agilex 7 FPGAs with R-Tile, First FPGA with PCIe 5.0 and CXL Capabilities
Breaking News
- Alphawave Semi announced today a refocussing of the Board of Directors after reaching the three-year milestone since the Company's IPO
- Synopsys and Samsung Electronics Collaborate to Achieve First Production Tapeout of Flagship Mobile CPU with Leading Performance on Samsung Foundry's GAA Process
- Worldwide Silicon Wafer Shipments Dip 5% in Q1 2024, SEMI Reports
- GOWIN's progress in global automotive market gathers momentum with award of ISO 26262 certification for its FPGA design environment
- PCI-SIG® Announces CopprLink™ Cable Specifications for PCIe® 5.0 and 6.0 Technology
Most Popular
- Silvaco Announces Launch of Initial Public Offering
- TSMC's A16 Process Moves Goalposts in Tech-Leadership Game
- Radiation-Tolerant PolarFire® SoC FPGAs Offer Low Power, Zero Configuration Upsets, RISC-V Architecture for Space Applications
- Synopsys Accelerates Next-Level Chip Innovation on TSMC Advanced Processes
- QuickLogic Releases Aurora 2.6 with Expanded Operating System Support and Up to 15% Faster Performance
E-mail This Article | Printer-Friendly Page |