Gate fusion applied to both forward and backward passes in quantum circuit simulation achieves 20-30x throughput gains and supports training large 20-qubit 1000-layer QML models with 60000 parameters using gradient checkpointing.
qHiPSTER: The Quantum High Performance Software Testing Environment
9 Pith papers cite this work, alongside 118 external citations. Polarity classification is still indexing.
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abstract
We present qHiPSTER, the Quantum High Performance Software Testing Environment. qHiPSTER is a distributed high-performance implementation of a quantum simulator on a classical computer, that can simulate general single-qubit gates and two-qubit controlled gates. We perform a number of single- and multi-node optimizations, including vectorization, multi-threading, cache blocking, as well as overlapping computation with communication. Using the TACC Stampede supercomputer, we simulate quantum circuits ("quantum software") of up to 40 qubits. We carry out a detailed performance analysis to show that our simulator achieves both high performance and high hardware efficiency, limited only by the sustainable memory and network bandwidth of the machine.
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Quantum circuit simulations on Apple M4 Pro show a reproducible 4.46x timing discontinuity at 29 qubits and access-pattern-dependent speedups (3.1-10x) that exceed peak bandwidth predictions.
PennyLane is a software library extending automatic differentiation to hybrid quantum-classical systems for variational quantum algorithms.
A binary-encoded, grouped-sparse Pauli engine (BinSim) runs large-scale variational and real-time quantum-chemistry emulations — up to 4.3×10^10 symmetry-adapted configurations — far faster than a Python reference.
TUSQ reduces redundant work in noisy quantum simulations via error tallying, commutation, importance sampling, and depth-first tree traversal with compute/uncompute reuse, reporting large speedups over Qiskit, CUDA-Q, and TQSim on 198 benchmarks.
SparQSim is a sparse-state quantum simulator in C++ supporting QRAM that outperforms dense Schrödinger simulators on high-sparsity benchmark circuits and produces consistent results for quantum linear system solvers.
Classical emulation of the HHL algorithm via extended UNIQuE scales exponentially only with qubit count and shows runtime advantage over state-vector simulation for small linear systems.
New merge booster and diagonal detector components, combined with cache blocking and gate fusion, deliver up to 160x speedup on circuit benchmarks and 34x on diagonal-heavy gates versus prior simulators.
Hybriqu Encoder delivers 5.4% faster pure angle encoding at 64 qubits on Apple Silicon by using AVX SIMD and cache-friendly precalculations, with gains increasing beyond L1 cache size while full-state updates remain memory-bound.
citing papers explorer
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Fast and memory-efficient classical simulation of quantum machine learning via forward and backward gate fusion
Gate fusion applied to both forward and backward passes in quantum circuit simulation achieves 20-30x throughput gains and supports training large 20-qubit 1000-layer QML models with 60000 parameters using gradient checkpointing.
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A Controlled Study of Memory Hierarchy Transitions in Quantum Circuit Simulation on Apple M4 Pro Unified Memory Architecture
Quantum circuit simulations on Apple M4 Pro show a reproducible 4.46x timing discontinuity at 29 qubits and access-pattern-dependent speedups (3.1-10x) that exceed peak bandwidth predictions.
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PennyLane: Automatic differentiation of hybrid quantum-classical computations
PennyLane is a software library extending automatic differentiation to hybrid quantum-classical systems for variational quantum algorithms.
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A High-Performance Pauli-Algebra Framework for Large-Scale Quantum Simulations
A binary-encoded, grouped-sparse Pauli engine (BinSim) runs large-scale variational and real-time quantum-chemistry emulations — up to 4.3×10^10 symmetry-adapted configurations — far faster than a Python reference.
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Noisy Quantum Simulation Using Tracking, Uncomputation and Sampling
TUSQ reduces redundant work in noisy quantum simulations via error tallying, commutation, importance sampling, and depth-first tree traversal with compute/uncompute reuse, reporting large speedups over Qiskit, CUDA-Q, and TQSim on 198 benchmarks.
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SparQSim: Simulating Scalable Quantum Algorithms via Sparse Quantum State Representations
SparQSim is a sparse-state quantum simulator in C++ supporting QRAM that outperforms dense Schrödinger simulators on high-sparsity benchmark circuits and produces consistent results for quantum linear system solvers.
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Extending UNIQuE: Quantum Simulation Speedup for the HHL Algorithm
Classical emulation of the HHL algorithm via extended UNIQuE scales exponentially only with qubit count and shows runtime advantage over state-vector simulation for small linear systems.
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Large-Scale Quantum Circuit Simulation on HPC Cluster via Cache Blocking, Boosting, and Gate Fusion Optimization
New merge booster and diagonal detector components, combined with cache blocking and gate fusion, deliver up to 160x speedup on circuit benchmarks and 34x on diagonal-heavy gates versus prior simulators.
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Accelerating Quantum State Encoding with SIMD: Design, Implementation, and Benchmarking
Hybriqu Encoder delivers 5.4% faster pure angle encoding at 64 qubits on Apple Silicon by using AVX SIMD and cache-friendly precalculations, with gains increasing beyond L1 cache size while full-state updates remain memory-bound.