SINTRONES RUGGED EDGE AI AMP INDUSTRIAL COMPUTING SOLUTIONS

AI and Computing Servers

AI and Computing Servers

Dell, HPE, Lenovo, and Supermicro are riding record AI server demand, but winning enterprise customers requires more than just Nvidia chips. Companies are building AI agents that write code and automate customer service, while moving from early experimentation to production deployment on other AI initiatives. These projects depend on foundation models from providers like OpenAI, Anthropic, and Llama, with every action triggering. Behind every smart AI algorithm is a powerhouse of raw computing: servers that process billions of calculations per second, data centers that consume as much power as small cities, and specialized hardware built to handle AI's relentless demands.

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Energy-efficient Raman amplifier for edge computing

Energy-efficient Raman amplifier for edge computing

The RAMAN accelerator is designed to leverage data and weight sparsity to deploy deep neural networks at the edge, ensuring low power consumption, minimal storage requirements, and reduced processing latency. To introduce novel solutions that can be viable for extreme edge cases, hybrid solutions combining conventional. Abstract—The shift from centralized cloud to edge comput-ing demands hardware systems with data processing capability at ultra-low power. Researchers at the Department of Electronic Systems Engineering, IISc, led by Chetan Singh Thakur, have developed an AI co-processor called RAMAN, or Re-configurable And sparse tinyML Accelerator for infereNce. This paper introduces the Modified Dadda Approximate Multiplier (MDAM), an innovative architecture that optimizes hardware economy.

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New optoelectronic fusion technology for edge computing

New optoelectronic fusion technology for edge computing

We have proposed the Fourier domain diffraction neural network, constructed the reconfigurable diffraction computing processor (DPU), developed the all-analog optoelectronic fusion computing chip ACCEL, and the large-scale general-purpose intelligent optoelectronic computing . We present GENIO, a novel platform that integrates edge computing within existing Passive Optical Network (PON) infrastructures. Integrating microelectronics and optoelectronics can harness the mature processes and functions of microelectronics, with the ultra-wideband and low-power benefits of optoelectronics.

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High-precision optical binning for edge computing

High-precision optical binning for edge computing

An adaptive optical power control and a shifted bins binning of the histogram (SBbH) method to achieve high-precision distance measurement both at short-range and long-range. Abstract: We experimentally realize photonic edge computing over an 86-km fiber link with 3 THz optical bandwidth and demonstrate DNN inference at 98. Machine learning is ubiquitous in cloud computing and data centers, but recently. Abstract—This paper demonstrates a ranging sensor system with a configurable array of 16 × 16 single photon avalanche diodes (SPADs), a 940nm vertical cavity surface-emitting laser (VCSEL), a co-design VCSEL driver with tunable widths from 400ps to 3630ps full-width at half-maximum (FWHM) optical. GENIO enhances central offices with computational and storage resources, enabling telecom operators to leverage their existing PON networks as a distributed edge. The proposed system combines distributed IoT sensors, blockchain-based secure data transmission, and neuromorphic.

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