We present a closed-loop method for determining the minimum of a viral rebound curve for an HIV patient undergoing a therapy transition. This method fits the parameters for a reduced approximate solution to the viral load measurements using a Simulated Annealing direct search algorithm. Gaussian white noise is added, and a family of fits is obtained. A safety tolerance measure is applied to the family of fits to obtain the next sample time. Using parameters identified from HIV data, we show that this method exhibits robust performance on noisy data generated from identified patient models, while greatly reducing the number of samples needed compared to a fixed-interval sampling approach.

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This paper presents the skip vector, a novel high-performance concurrent data structure based on the skip list. Traversal is sped up by flattening the layers of the skip list into vectors, avoiding much of the costly pointer chasing that skip lists incur. The skip vector utilizes optimistic traversal with sequence locks, and hazard pointers for fast, memory-safe, concurrent access. In microbenchmark evaluation, we show that the skip vector offers excellent performance across a range of key ranges, thread counts, and operation mixes. CCS CONCEPTS • Computing methodologies → Concurrent algorithms.