ASPLOS'23 - Session 5C - Betty: Enabling Large-Scale GNN Training with Batch-Level Graph Partitionin
ASPLOS
ASPLOS'23 - Session 5C - TensorIR: An Abstraction for Automatic Tensorized Program Optimization
ASPLOS
ASPLOS'23 - Session 5C - FLAT: An Optimized Dataflow for Mitigating Attention Bottlenecks
ASPLOS
ASPLOS'23 - Session 5B - Prism: Optimizing Key-Value Store for Modern Heterogeneous Storage Devices
ASPLOS
ASPLOS'23 - Session 5C - TLP: A Deep Learning-based Cost Model for Tensor Program Tuning
ASPLOS
ASPLOS'23 - Session 5B - Reconfigurable Virtual Memory for FPGA-Driven I/O
ASPLOS
ASPLOS'23 - Session 5B - Re-architecting I/O Caches for Emerging Fast Storage Devices
ASPLOS
ASPLOS'23 - Session 5C - Homunculus: Auto-Generating Efficient Data-Plane ML Pipelines for Datacente
ASPLOS
ASPLOS'23 - Session 5A - Vidi: Record Replay for Reconfigurable Hardware
ASPLOS
ASPLOS'23 - Session 5C - Mobius: Fine Tuning Large-scale Models on Commodity GPU Servers
ASPLOS
ASPLOS'23 - Session 5A - DrGPUM: Guiding Memory Optimization for GPU-accelerated Applications
ASPLOS
ASPLOS'23 - Session 3A - Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenter
ASPLOS
ASPLOS'23 - Session 7B - Protect the System Call, Protect (most of) the World with BASTION
ASPLOS