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Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various tasks. However, their substantial computational and memory requirements present challenges, especially for devices…

Aligning future system design with the ever-increasing compute needs of large language models (LLMs) is undoubtedly an important problem in today's world. Here, we propose a general performance modeling methodology and workload analysis of…

Hardware Architecture · Computer Science 2024-07-23 Joyjit Kundu , Wenzhe Guo , Ali BanaGozar , Udari De Alwis , Sourav Sengupta , Puneet Gupta , Arindam Mallik

Large Language Models (LLMs) have seen great advance in both academia and industry, and their popularity results in numerous open-source frameworks and techniques in accelerating LLM pre-training, fine-tuning, and inference. Training and…

Performance · Computer Science 2023-12-04 Longteng Zhang , Xiang Liu , Zeyu Li , Xinglin Pan , Peijie Dong , Ruibo Fan , Rui Guo , Xin Wang , Qiong Luo , Shaohuai Shi , Xiaowen Chu

Large Language Models (LLMs) have become extremely potent instruments with exceptional capacities for comprehending and producing human-like text in a wide range of applications. However, the increasing size and complexity of LLMs present…

Machine Learning · Computer Science 2024-06-18 Yingbing Huang , Lily Jiaxin Wan , Hanchen Ye , Manvi Jha , Jinghua Wang , Yuhong Li , Xiaofan Zhang , Deming Chen

Large Language Models (LLMs) have significantly advanced artificial intelligence by optimizing traditional Natural Language Processing (NLP) workflows, facilitating their integration into various systems. Many such NLP systems, including…

Computation and Language · Computer Science 2025-05-13 Jiliang Ni , Jiachen Pu , Zhongyi Yang , Kun Zhou , Hui Wang , Xiaoliang Xiao , Dakui Wang , Xin Li , Jingfeng Luo , Conggang Hu

Large Language Models (LLMs) herald a transformative era in artificial intelligence (AI). However, the expansive scale of data and parameters of LLMs requires high-demand computational and memory resources, restricting their accessibility…

Machine Learning · Computer Science 2024-11-26 Shengwen Ding , Chenhui Hu

As large language models (LLMs) scale in size and adoption, their computational and environmental costs continue to rise. Prior benchmarking efforts have primarily focused on latency reduction in idealized settings, often overlooking the…

Computation and Language · Computer Science 2025-04-25 Jared Fernandez , Clara Na , Vashisth Tiwari , Yonatan Bisk , Sasha Luccioni , Emma Strubell

The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There's an increasing focus on cost-efficient training and deployment within this context.…

In recent years, large language models (LLMs) have achieved remarkable success in natural language processing (NLP). LLMs require an extreme amount of parameters to attain high performance. As models grow into the trillion-parameter range,…

Computation and Language · Computer Science 2024-09-10 Zhyar Rzgar K Rostam , Sándor Szénási , Gábor Kertész

Large language models (LLMs) are widely applied in chatbots, code generators, and search engines. Workload such as chain-of-throught, complex reasoning, agent services significantly increase the inference cost by invoke the model…

Computation and Language · Computer Science 2025-11-27 Sihyeong Park , Sungryeol Jeon , Chaelyn Lee , Seokhun Jeon , Byung-Soo Kim , Jemin Lee

Large language models (LLMs) have exploded in popularity due to their new generative capabilities that go far beyond prior state-of-the-art. These technologies are increasingly being leveraged in various domains such as law, finance, and…

Large language models (LLMs) are increasingly recognized for their exceptional generative capabilities and versatility across various tasks. However, the high inference costs associated with these models have not received adequate…

Computation and Language · Computer Science 2025-03-18 Soham Poddar , Paramita Koley , Janardan Misra , Sanjay Podder , Niloy Ganguly , Saptarshi Ghosh

With the rapid growth of large language models (LLMs), a wide range of methods have been developed to distribute computation and memory across hardware devices for efficient training and inference. While existing surveys provide descriptive…

Machine Learning · Computer Science 2026-02-11 Hossam Amer , Rezaul Karim , Ali Pourranjbar , Weiwei Zhang , Walid Ahmed , Boxing Chen

Large Language Models (LLMs) have attracted extensive attention due to their remarkable performance across various tasks. However, the substantial computational and memory requirements of LLM inference pose challenges for deployment in…

The rapid growth of Large Language Models (LLMs) has been a driving force in transforming various domains, reshaping the artificial general intelligence landscape. However, the increasing computational and memory demands of these models…

Computation and Language · Computer Science 2024-04-22 Tianyu Ding , Tianyi Chen , Haidong Zhu , Jiachen Jiang , Yiqi Zhong , Jinxin Zhou , Guangzhi Wang , Zhihui Zhu , Ilya Zharkov , Luming Liang

The proliferation of large language models (LLMs) with varying computational costs and performance profiles presents a critical challenge for scalable, cost-effective deployment in real-world applications. We introduce a unified routing…

The prohibitive training costs of Large Language Models (LLMs) have emerged as a significant bottleneck in the development of next-generation LLMs. In this paper, we show that it is possible to significantly reduce the training costs of…

Computation and Language · Computer Science 2025-05-16 Chenze Shao , Fandong Meng , Jie Zhou

As modern artificial intelligence (AI) systems become more advanced and capable, they can leverage a wide range of tools and models to perform complex tasks. The task of orchestrating these models is increasingly performed by Large Language…

Artificial Intelligence · Computer Science 2026-04-20 Daria Smirnova , Hamid Nasiri , Marta Adamska , Zhengxin Yu , Peter Garraghan

Large language models (LLMs) have been a disruptive innovation in recent years, and they play a crucial role in our daily lives due to their ability to understand and generate human-like text. Their capabilities include natural language…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-10-17 Akrit Mudvari , Yuang Jiang , Leandros Tassiulas

Large language models (LLMs) power many state-of-the-art systems in natural language processing. However, these models are extremely computationally expensive, even at inference time, raising the natural question: when is the extra cost of…

Machine Learning · Computer Science 2023-05-05 Deepak Narayanan , Keshav Santhanam , Peter Henderson , Rishi Bommasani , Tony Lee , Percy Liang
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