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