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Task pools have many important applications in distributed and parallel computing. Pools are typically implemented using concurrent queues, which limits their scalability. We introduce CAFÉ, Contention and Fairness Explorer, a scalable and wait-free task pool which allows users to control the trade-off between fairness and contention. The main idea behind(More)
Modern big data processing platforms employ huge in-memory key-value (KV-) maps. Their applications simultaneously drive high-rate data ingestion and large-scale analytics. These two scenarios expect KV-map implementations that scale well with both real-time updates and massive atomic scans triggered by range queries. However, today's state-of-the art(More)
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