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Explore Unity, a system optimizing distributed DNN training through joint algebraic transformations and parallelization. Learn about its unified parallel computation graph and hierarchical search algorithm for improved performance.
Explores metastable failures in distributed systems, analyzing real-world incidents to categorize triggers and amplification mechanisms, aiding understanding and potential solutions for this prevalent issue.
Automating device driver isolation to protect kernels from vulnerabilities, using CPU extensions for low-overhead implementation and advanced analyses to identify shared state and synchronization requirements.
Introduces ROLLER, a fast tensor compilation approach for deep learning using rTile abstraction and recursive construction, generating efficient kernels in seconds for various accelerators.
Explore Knox, a framework for building verified hardware security modules (HSMs) that eliminates bugs and side channels through formal verification and information-preserving refinement.
Explore zero-change object transmission for efficient data exchange in distributed big data analytics, improving performance without code modifications.
Microsecond-scale RDMA control plane for elastic computing, enabling rapid connection establishment and efficient data transfer in distributed systems and serverless environments.
Explore ECOS, an enterprise-centric offloading system for mobile applications, addressing privacy concerns and resource management to improve handheld device performance and energy efficiency.
Runtime programmable switches enabling partial reconfiguration of network data planes without service disruption. FlexCore design allows flexible updates with consistency guarantees, demonstrating feasibility and benefits for future networks.
Innovative framework for optimizing network-wide monitoring in diverse, dynamic environments. Reduces resource overhead while maintaining performance, coverage, and accuracy through automated profiling and task allocation.
Automated technique for verifying network function binaries without source code, using ghost maps to model data structures and infer control flow, enabling operators to ensure reliability of proprietary software.
Explores Swift, an adaptive video streaming system using layered neural codecs for fine-grained rate adaptation, offering improved compression and decoding efficiency over traditional layered coding approaches.
Innovative task sampling approach for cluster job scheduling, improving runtime property estimation and reducing job completion time compared to history-based predictors.
Accelerates container provisioning for edge and WAN environments by redesigning deployment protocols, filesystem, and image storage, achieving 3x faster deployment with minimal overhead.
Explore privacy-preserving video analytics with Privid, a system enforcing duration-based privacy for public surveillance footage while maintaining utility for various applications.
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