Distributed Computing
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FastMPS: A Multi-Level Parallel Framework for Scalable Matrix Product State Sampling
FastMPS addresses limitations in large-scale Matrix Product State (MPS) sampling by integrating data parallelism across samples with tensor parallelism along bond dimensions. This novel approach mitigates memory and I/O bottlenecks through compression and overlapping, effectively reactivating data p…
Parallelization Strategies for IPOP-CMA-ES Achieve Superlinear Speedups
This paper details methods for accelerating the IPOP-CMA-ES algorithm on high-performance computing architectures. By integrating BLAS/LAPACK routines and employing two distinct parallelization strategiesâsequential-ordering and concurrent processingâthe researchers achieved substantial, includi…