Abstract: The importance of Model Parallelism in Distributed Deep Learning continues to grow due to the increase in the Deep Neural Network (DNN) scale and the demand for higher training speed.

This repository contains the implementation of HD-MoE, a hybrid and dynamic parallelism framework designed to optimize Mixture-of-Experts (MoE) Large Language Model (LLM) inference on 3D Near-Memory ...

Abstract: Current deep learning compilers have made significant strides in optimizing computation graphs for single- and multi-model scenarios. However, they lack specific optimizations for ...

Every ChatGPT query, every AI agent action, every generated video is based on inference. Training a model is a one-time ...

JIT compiler stack up against PyPy? We ran side-by-side benchmarks to find out, and the answers may surprise you.

Python will be the fourth officially-supported language in the OpenMP API; Leading Python infrastructure company Anaconda ...

Centralized migration accelerates adaptation and drives parallel evolution, emphasizing the key influence of spatial organization on evolutionary dynamics across systems from pathogen transmission to ...

Most teams don’t think about CI bills until something changes: a heavier test matrix, macOS jobs, or bigger runners. On the surface, GitHub Actions can be $0, ...

Kimi K2.5 adds Agent Swarm with up to 100 parallel helpers and a 256k window, so teams solve complex work faster.

Western Digital has presented a set of HDD design changes that focus on boosting I/O throughput without abandoning the ...

Biocomputing research is testing living neurons for computation as scientists look for energy-efficient alternatives to ...