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From google gemini to openai q*(q-star): A survey of resha** the generative artificial intelligence (ai) research landscape
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
A survey on scheduling techniques in computing and network convergence
The computing demand for massive applications has led to the ubiquitous deployment of
computing power. This trend results in the urgent need for higher-level computing resource …
computing power. This trend results in the urgent need for higher-level computing resource …
A survey on mixture of experts
Large language models (LLMs) have garnered unprecedented advancements across
diverse fields, ranging from natural language processing to computer vision and beyond …
diverse fields, ranging from natural language processing to computer vision and beyond …
Megablocks: Efficient sparse training with mixture-of-experts
We present MegaBlocks, a system for efficient Mixture-of-Experts (MoE) training on GPUs.
Our system ismotivated by the limitations of current frameworks, which restrict the dynamic …
Our system ismotivated by the limitations of current frameworks, which restrict the dynamic …
Enhancing simplified chinese poetry comprehension in llama-7b: A novel approach to mimic mixture of experts effect
Y Zhang, X Chen - 2023 - researchsquare.com
This study explored the potential of manual augmentation in enhancing the comprehension
and translation capabilities of large language models, specifically focusing on the LLaMA …
and translation capabilities of large language models, specifically focusing on the LLaMA …
Accelerating distributed {MoE} training and inference with lina
Scaling model parameters improves model quality at the price of high computation
overhead. Sparsely activated models, usually in the form of Mixture of Experts (MoE) …
overhead. Sparsely activated models, usually in the form of Mixture of Experts (MoE) …
Pre-gated moe: An algorithm-system co-design for fast and scalable mixture-of-expert inference
Large language models (LLMs) based on transformers have made significant strides in
recent years, the success of which is driven by scaling up their model size. Despite their high …
recent years, the success of which is driven by scaling up their model size. Despite their high …
Schemoe: An extensible mixture-of-experts distributed training system with tasks scheduling
In recent years, large-scale models can be easily scaled to trillions of parameters with
sparsely activated mixture-of-experts (MoE), which significantly improves the model quality …
sparsely activated mixture-of-experts (MoE), which significantly improves the model quality …
Janus: A unified distributed training framework for sparse mixture-of-experts models
Scaling models to large sizes to improve performance has led a trend in deep learning, and
sparsely activated Mixture-of-Expert (MoE) is a promising architecture to scale models …
sparsely activated Mixture-of-Expert (MoE) is a promising architecture to scale models …
A hybrid tensor-expert-data parallelism approach to optimize mixture-of-experts training
Mixture-of-Experts (MoE) is a neural network architecture that adds sparsely activated expert
blocks to a base model, increasing the number of parameters without impacting …
blocks to a base model, increasing the number of parameters without impacting …