Delves into challenges of real-time decision-making in data-intensive systems, covering query-driven data sanitization, hardware optimization, and GPU data access.
Explores scalable synchronization mechanisms for many-core operating systems, focusing on the challenges of handling data growth and regressions in OS.
Covers the adaptation of analytics systems to modern hardware and data challenges, focusing on efficiency and scalability through innovative approaches and hybrid systems.
Explores the use of fast interconnects for scalable co-processing with GPUs in databases, emphasizing the importance of overcoming the transfer bottleneck and reevaluating assumptions for performance improvements.
Explores storage management challenges in transitioning to data lakes, addressing software and hardware heterogeneity, unified storage design, and performance optimization.
