Intel to Acquire Deep Learning Nervana
Nervana neural chip part of the deal
R. Colin Johnson, EETimes
8/10/2016 08:47 PM EDT
LAKE WALES, Fla.—Intel will announce its intention to acquire Nervana Systems at its Intel Developer Forum next week (IDF 2016, San Francisco, Calif., August 16-to-18)—a bid to obsolete the graphics processor unit (GPU) for deep learning artificial intelligence (AI) applications.
Intel dominates the high-performance computing (HPC) market, but Nvidia has made significant inroads into deep learning verticals with its sophisticated GPUs. However, Nervana Systems (Palo Alto, Calif.) has already made a significant dent in Nvidia's Cuda software for its GPUs with Nervana's Neon cloud service that is Cuda-compatible. Intel, however, is acquiring Nervana for its promised deep-learning accelerator chip, which it promises by 2017. If the chip plays out as advertised, Intel will sell Deep Learning accelerator hardware boards that beat Nvidia's GPU boards, while its newly acquired Neon cloud service will outperform Nvidia's Cuda software.
E-mail This Article | Printer-Friendly Page |
|
Related News
Breaking News
- Ubitium Debuts First Universal RISC-V Processor to Enable AI at No Additional Cost, as It Raises $3.7M
- TSMC drives A16, 3D process technology
- Frontgrade Gaisler Unveils GR716B, a New Standard in Space-Grade Microcontrollers
- Blueshift Memory launches BlueFive processor, accelerating computation by up to 50 times and saving up to 65% energy
- Eliyan Ports Industry's Highest Performing PHY to Samsung Foundry SF4X Process Node, Achieving up to 40 Gbps Bandwidth at Unprecedented Power Levels with UCIe-Compliant Chiplet Interconnect Technology
Most Popular
- Cadence Unveils Arm-Based System Chiplet
- CXL Fabless Startup Panmnesia Secures Over $60M in Series A Funding, Aiming to Lead the CXL Switch Silicon Chip and CXL IP
- Esperanto Technologies and NEC Cooperate on Initiative to Advance Next Generation RISC-V Chips and Software Solutions for HPC
- Eliyan Ports Industry's Highest Performing PHY to Samsung Foundry SF4X Process Node, Achieving up to 40 Gbps Bandwidth at Unprecedented Power Levels with UCIe-Compliant Chiplet Interconnect Technology
- Arteris Selected by GigaDevice for Development in Next-Generation Automotive SoC With Enhanced FuSa Standards