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Found 5 papers, 0 papers with code
TP-Aware Dequantization
In this paper, we present a novel method that reduces model inference latency during distributed deployment of Large Language Models (LLMs).
Accelerating a Triton Fused Kernel for W4A16 Quantized Inference with SplitK work decomposition
Our implementation shows improvement for the type of skinny matrix-matrix multiplications found in foundation model inference workloads.
AI-aided multiscale modeling of physiologically-significant blood clots
We have developed an AI-aided multiple time stepping (AI-MTS) algorithm and multiscale modeling framework (AI-MSM) and implemented them on the Summit-like supercomputer, AIMOS.
CASTELO: Clustered Atom Subtypes aidEd Lead Optimization -- a combined machine learning and molecular modeling method
Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials.
Accelerating Data Loading in Deep Neural Network Training
Our model suggests that I/O rate limits the scalability of distributed training, which inspires us to design a locality-aware data loading method.
