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Continuous fuzzing technique for enterprise-level DBMSs, addressing challenges in SQL grammar, codebase evolution, and anomaly analysis. Discovered 236 bugs across 12 major DBMSs.
Efficient distributed training system for heterogeneous GPUs. Optimizes parallelism plans, improves resource utilization, and achieves significant speed-ups for large deep learning models.
Innovative approach using filesystems for extensible memory management, enabling diverse memory configurations and policies with minimal code and competitive performance.
Innovative OS scheduler for serverless functions, combining SRPT and proportional-share scheduling to optimize performance of short-lived tasks while preventing starvation of longer functions.
Innovative GPU kernel design enables efficient 6-bit quantization for large language models, significantly improving inference speed while maintaining quality across various applications.
Explores OSMOSIS, a resource manager enabling multi-tenancy in SmartNICs. Demonstrates dynamic hardware resource multiplexing for on-path packet processing, supporting broader adoption in datacenters with low overhead.
Innovative GPU sandbox for serverless inference, reducing memory footprint and improving throughput. Enhances DNN inference serving with efficient memory management and intra-GPU communication.
Innovative solution for addressing hot bloat in virtualization, improving performance and memory efficiency. HugeScope offers lightweight, effective framework for page tracking, splitting, and coalescing on commodity hardware.
Explores UniMem, a novel disaggregated memory system that optimizes remote memory access, local cache utilization, and page migration for improved performance in large-scale computing environments.
Explores innovative approach to intermittent computation for energy harvesting devices, introducing Camel system for efficient state management and improved performance on Flash-based platforms.
Innovative approach to optimize Ethereum archive nodes, reducing storage by 98.1% and improving performance through compacted, flattened, and fine-grained historical state maintenance.
Explores HydraRPC, utilizing CXL-attached HDM for efficient data transmission, eliminating network rounds and memory copying. Evaluates performance on real CXL hardware, showcasing potential for building efficient RPC systems.
Innovative hybrid cloud scheduler maximizing cluster utilization, reducing cloud costs by 54-91% while minimizing job completion time impact through dynamic waiting time control and configurable resource management.
Innovative folio accounting technique for Linux enhances memory management, improving performance in fork and unmap operations. Demonstrates significant speedup in fork-intensive workloads like Redis.
Proactive validation system enhancing cloud AI infrastructure reliability by mitigating hidden degradation, featuring comprehensive benchmarks and intelligent component evaluation for optimal performance.
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