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FedPLT: Scalable, Resource-Efficient, and Heterogeneity-Aware Federated Learning via Partial Layer Training
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Taming Request Imbalance: SLO-Aware Scheduling for Disaggregated LLM Inference
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Leveraging Teaching on Demand: Approaching HPC to Undergrads
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A Treasure Trove of Performance: Analyzing the IO500 Submission Data
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PipeMax: Enhancing Offline LLM Inference on Commodity GPU Servers
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Heterogeneous Model Fusion for Privacy-Aware Multi-Camera Surveillance via Synthetic Domain Adaptation
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FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training
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On the Distortion of Partitioning Performance by Random Quantum Circuits
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Cross-Layer Energy Analysis of Multimodal Training on Grace Hopper Superchips
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Decentralized Stratified Sampling for Low-Latency Approximate Geospatial Data Stream Processing in Edge-Cloud Architectures
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Stochastic Sparse Attention for Memory-Bound Inference
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nvPAX: Constrained Optimization for Dynamic Power Allocation in Hierarchical and Multi-Tenant Systems
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Joint Temporal-Structural Representation Learning for Distributed Fault Discrimination in Microservice Architectures
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SplitZip: Ultra Fast Lossless KV Compression for Disaggregated LLM Serving
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CvxCluster: Solving Large, Complex, Granular Resource Allocation Problems 100-1000x Faster
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MANOJAVAM: A Scalable, Unified FPGA Accelerator for Matrix Multiplication and Singular Value Decomposition in Principal Component Analysis
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VUDA: Breaking CUDA-Vulkan Isolation for Spatial Sharing of Compute and Graphics on the Same GPU
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Implementing True MPI Sessions and Evaluating MPI Initialization Scalability
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Surviving the Edge: Federated Learning under Networking and Resource Constraints
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Lifting to tensors when compiling scientific computing workloads for AI Engines
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