SPEC CPU 2026 presents a new benchmark suite using open-source apps, expanded multithreading, and Rolling-Round-Robin Rate to address gaps in evaluating heterogeneous multiprogrammed CPU performance.
Bartz-Beielstein et al.,Benchmarking in Optimization: Best Practice and Open Issues
6 Pith papers cite this work, alongside 81 external citations. Polarity classification is still indexing.
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Block-Bench constructs controllable discrete optimization benchmarks from block functions and dependency graphs to enable transparent analysis of algorithm behavior beyond the objective value.
Supervised classifiers trained on 23 features from Nevergrad runs on COCO can detect unreliable run-number estimates with high minority-class recall in within-optimizer settings.
The authors adapt an existing standard into a unified description framework for multi-energy systems case studies, apply it to diverse cases, and develop a review checklist through cross-author evaluation.
Hyperparameter optimization yields performance improvements for recombination-based Cartesian Genetic Programming on SRBench.
Asymmetry PRISM-CPU achieves 4.5x-24.1x speedups over reference solvers on N=100-2000 problems and GPU completes all 500 accounts in 109.5s where OSQP completes 4.
citing papers explorer
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SPEC CPU: The Next Generation
SPEC CPU 2026 presents a new benchmark suite using open-source apps, expanded multithreading, and Rolling-Round-Robin Rate to address gaps in evaluating heterogeneous multiprogrammed CPU performance.
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Block-Bench: A Framework for Controllable and Transparent Discrete Optimization Benchmarking
Block-Bench constructs controllable discrete optimization benchmarks from block functions and dependency graphs to enable transparent analysis of algorithm behavior beyond the objective value.
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Learning to Assess the Reliability of Number-of-Runs Estimation in Stochastic Optimization
Supervised classifiers trained on 23 features from Nevergrad runs on COCO can detect unreliable run-number estimates with high minority-class recall in within-optimizer settings.
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Standardizing case study descriptions for multi-energy systems and networks modeling
The authors adapt an existing standard into a unified description framework for multi-energy systems case studies, apply it to diverse cases, and develop a review checklist through cross-author evaluation.
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Improving Evaluation of Recombination-based Cartesian Genetic Programming
Hyperparameter optimization yields performance improvements for recombination-based Cartesian Genetic Programming on SRBench.
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Asymmetry PRISM: A CPU/GPU Portfolio Optimization Engine for Deadline-Bounded Institutional Rebalancing
Asymmetry PRISM-CPU achieves 4.5x-24.1x speedups over reference solvers on N=100-2000 problems and GPU completes all 500 accounts in 109.5s where OSQP completes 4.