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Bridging Realities: CUDA-Q's MLIR Pipeline for Quantum-Classical Hybrid Computing
DescriptionThe integration of quantum processing units (QPUs) with high-performance computing (HPC) infrastructures represents one of the most significant challenges in quantum computing today. As quantum systems scale beyond the NISQ era toward utility-scale applications, the need for robust, performance-optimized compilation toolchains becomes critical for realizing quantum advantage in real-world scientific computing workflows.
Quantum compilation fundamentally differs from classical compilation in ways that challenge traditional compiler design principles. While classical compilers optimize for performance metrics like instruction throughput and cache locality, quantum compilers must navigate the fragile nature of quantum superposition, where measurement destroys quantum states and decoherence imposes strict timing constraints. Quantum programs exhibit unique characteristics: some of their pieces (the quantum circuits) are inherently reversible, programs operate on exponentially large Hilbert spaces and require hardware-specific gate decompositions that vary dramatically across QPU architectures.
This talk presents some of the challenges in quantum compilation and CUDA-Q's approach to quantum-classical hybrid compilation through its sophisticated MLIR-based compiler infrastructure that seamlessly integrates quantum kernels with HPC environments. We will talk about how CUDA-Q leverages the Multi-Level Intermediate Representation (MLIR) framework to enable progressive lowering from high-level C++ and Python quantum programs through multiple abstraction layers.
Quantum compilation fundamentally differs from classical compilation in ways that challenge traditional compiler design principles. While classical compilers optimize for performance metrics like instruction throughput and cache locality, quantum compilers must navigate the fragile nature of quantum superposition, where measurement destroys quantum states and decoherence imposes strict timing constraints. Quantum programs exhibit unique characteristics: some of their pieces (the quantum circuits) are inherently reversible, programs operate on exponentially large Hilbert spaces and require hardware-specific gate decompositions that vary dramatically across QPU architectures.
This talk presents some of the challenges in quantum compilation and CUDA-Q's approach to quantum-classical hybrid compilation through its sophisticated MLIR-based compiler infrastructure that seamlessly integrates quantum kernels with HPC environments. We will talk about how CUDA-Q leverages the Multi-Level Intermediate Representation (MLIR) framework to enable progressive lowering from high-level C++ and Python quantum programs through multiple abstraction layers.
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