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Practical online learning system for in-network ML models, addressing automatic labeling and efficient performance monitoring. Improves model adaptability to dynamic network environments.
Optimizes ML inference systems by maximizing GPU resource utilization and minimizing interference, resulting in higher goodput and cost-efficiency for deep learning model deployment.
Innovative memory management strategy for tiered systems, improving performance under pressure through non-exclusive page retention and transactional migration.
Innovative I/O scheduling system for cloud block storage, enhancing performance and reducing latency. Utilizes data processing units and queue scaling to improve load balancing and mitigate tenant interference.
Innovative system for efficient distributed transactions on disaggregated memory, improving throughput and reducing latency through multi-versioning and RDMA-based protocols.
Innovative ransomware protection system for cloud block stores. DeftPunk uses two-layer classification, strategic snapshots, and log-structured support for efficient detection and recovery with minimal data loss.
Explore HongMeng, a general-purpose microkernel addressing performance and compatibility challenges while maintaining security and reliability for smartphones and smart vehicles.
Innovative system for efficient LLM serving, using dynamic rescheduling to improve load balancing, resource utilization, and request prioritization, resulting in better performance and cost savings.
Innovative compiler for optimizing low-precision deep learning computations, bridging custom data types with hardware limitations to enhance performance without hardware modifications.
Innovative distributed lock service using programmable switches for improved latency and throughput, supporting millions of locks through lock fission and on-demand migration techniques.
Explores hardware-managed memory tiering with CXL, introducing Intel® Flat Memory Mode and Memstrata allocator to optimize performance and reduce contention in virtualized cloud environments.
Explore RefFS, a groundbreaking concurrent file system with proven liveness and safety. Learn about dynamically layered definite releases and the MoLi framework for verifying concurrent systems.
Innovative framework for enhancing formal specification reliability through automated testing, SpecTesting Proofs, and mutation testing. Discovers bugs in real-world verified systems, strengthening software verification.
Streamlining distributed protocol proofs using invariant taxonomies. Simplifies finding inductive invariants by categorizing them into Regular and Protocol Invariants, reducing developer effort in proving correctness.
Innovative protocol for capturing partial snapshots in distributed cloud services, ensuring causal consistency without disrupting operations. Leverages load balancers for minimal changes and near-zero overhead.
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