Thermal Simulation And Optimization in 3D-IC Design (Intel, UCSB, Cadence)


A new technical paper titled "DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design" was published by researchers at Intel Corporation, University of California, Santa Barbara and Cadence. Abstract "Thermal analysis is crucial in 3D-IC design due to increased power density and complex heat dissipation paths. Although operator ... » read more

Optimizing LLM Training Under GPU Memory Constraints (Argonne, RIT)


A new technical paper titled "MLP-Offload: Multi-Level, Multi-Path Offloading for LLM Pre-training to Break the GPU Memory Wall" was published by researchers at Argonne National Laboratory and Rochester Institute of Technology. Abstract "Training LLMs larger than the aggregated memory of multiple GPUs is increasingly necessary due to the faster growth of LLM sizes compared to GPU memory. To... » read more

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)


A new technical paper titled "Pie: Pooling CPU Memory for LLM Inference" was published by researchers at UC Berkeley. Abstract "The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill over to CPU memory; however, traditional GPU-CPU memory swapping ofte... » read more