qshan / DL-on-Silicon

research, experimentation and implementation of hardware-agnostic accelerated DL framework

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• Review Papers
• AI-accelerators(CPU, GPU, FPGA, ASIC, SoC, HPC), Neuromorphic and Quantum Compute for AI
• case study: ml/dl frameworks/libraries(an architectural overview)
• deep learning compiler Optimization for different hardwares
• New Theories of Computation
• Demystifying Deep Learning Frameworks and Libraries(end to end low+high level)
• Neural Networks on Silicon
• Embedded-Neural-Network

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