future

**Future Trends Parallel Computing Post-Moore** is **a forward-looking analysis of emerging computational paradigms, specialized processors, and system architectures transcending Moore's Law limitations and addressing next-generation computing challenges** — Post-Moore computing addresses transistor scaling slowdown requiring novel approaches to continued performance improvement. **Domain-Specific Processors** specializes hardware for specific application domains (AI, HPC, graphics), delivers better performance-per-watt than general-purpose processors. **Quantum Computing** exploits quantum mechanical effects enabling exponential speedups for optimization, simulation, and factoring problems, requires quantum-classical hybrid systems. **Optical Computing** leverages photons for information processing and communication, promises superior speed and energy efficiency compared to electronic alternatives. **Neuromorphic Computing** implements brain-inspired architectures achieving human-level efficiency and learning, enables on-device learning and personalization. **Analog Computing** returns to analog computation for specific workloads, promises energy efficiency and reduced latency compared to digital processing. **In-Memory Computing** eliminates von Neumann bottleneck through memory-based computation, enables massive parallelism within dense memory systems. **System Integration** emphasizes heterogeneous integration combining multiple processors, uses chiplet approaches enabling diverse process nodes and technologies. **Software Paradigm Shifts** requires new programming models exploiting massive parallelism, probabilistic computation, and approximate algorithms. **Future Trends Parallel Computing Post-Moore** envisions diverse specialized systems replacing homogeneous processors as computing paradigm.