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Comprehensive study on accelerating erasure coding for data storage, exploring optimization techniques, bitmatrix design, and vectorization to improve computation efficiency and performance in various scenarios.
Explores efficient graph processing on emerging storage devices, proposing a new partitioning framework that leverages improved random access capabilities for 2X better performance than state-of-the-art solutions.
ScaleCheck: A novel approach for finding scalability bugs in large distributed systems using program analysis and colocation techniques, enabling testing at scale on a single commodity PC.
Explores design tradeoffs in SSD reliability techniques, proposing a holistic management scheme for balancing performance, reliability, and lifetime across various workloads and wear states.
Explores Ziggurat, a tiered file system combining NVMM and disks for high performance and capacity. Discusses data placement, synchronicity prediction, and cold data migration to optimize storage efficiency.
GraphOne: A data store for real-time analytics on evolving graphs, combining edge and adjacency lists with dual versioning for efficient updates and computations. Outperforms graph databases in ingestion and static graph systems in analytics.
Innovative distributed caching mechanism providing provable load balancing for large-scale storage systems. Partitions hot objects and adaptively routes queries, enabling linear cache throughput increase with node count.
Optimizing hash-based indexing for persistent memory: CCEH reduces overhead, guarantees constant lookup time, and ensures failure-atomicity without explicit logging, improving query latency compared to existing techniques.
Optimizing data structures and memory allocation to reduce bit flipping in byte-addressable non-volatile memory, improving power efficiency and memory longevity without compromising performance.
Hybrid key-value cache system using DRAM and SSD to reduce flash write amplification, improving SSD durability for cloud databases while maintaining performance and efficiency.
Automated inference of behavioral models for stateful network functions, enabling accurate testing and verification. Introduces Alembic, which synthesizes finite-state machine ensembles for diverse rule types and configurations.
Efficient RPC library for datacenter networks offering high performance without sacrificing generality. Handles packet loss and congestion while achieving low latency and high bandwidth on commodity hardware.
Innovative 3D localization system for precise robotic tasks, achieving sub-centimeter accuracy and low latency through advanced bandwidth extraction and Bayesian algorithms, enabling real-time applications.
Explore reconfiguring wireless environments with large arrays of inexpensive antennas to improve communication. Innovative approach achieves significant throughput and capacity gains in real indoor settings.
Federated resource management system for large-scale data analytics, enabling efficient scheduling and policy enforcement across millions of cores and exabytes of data in Microsoft's internal data lake.
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