The IoMT is a device that works with different healthcare systems to help develop networking technologies. It reduces the unnecessary burden of visiting the hospital. Instead, it enables the transfer of medical relate...
详细信息
The proposed work uses NLP (Natural Language Processing) techniques for detecting the misleading news stories that come from the non-reputable sources. The proposed model has three stages, data collection phase, data ...
详细信息
The "Anti-Sleep Glasses" uses artificial intelligence (AI) to solve the serious problem of accidents caused by *** system uses an ESP32 AI Cam board and customized glasses to integrate a machine learning (ML...
详细信息
Forest fires are a serious hazard to both the environment and human life. For an effective and timely response, early detection of these fires is essential. This study offers a reliable method for detecting forest fir...
详细信息
Artificial intelligence and deep learning are becoming an inevitable part of our life. Deep learning models are giving contributions to the identification of genetic causes behind various diseases affecting the human ...
详细信息
Efficiently serving large language models (LLMs) requires batching many requests together to reduce the cost per request. Yet, the key-value (KV) cache, which stores attention keys and values to avoid re-computations,...
详细信息
Efficiently serving large language models (LLMs) requires batching many requests together to reduce the cost per request. Yet, the key-value (KV) cache, which stores attention keys and values to avoid re-computations, significantly increases memory demands and becomes the new bottleneck in speed and memory usage. This memory demand increases with larger batch sizes and longer context lengths. Additionally, the inference speed is limited by the size of KV cache, as the GPU's SRAM must load the entire KV cache from the main GPU memory for each token generated, causing the computational core to be idle during this process. A straightforward and effective solution to reduce KV cache size is quantization, which decreases the total bytes taken by KV cache. However, there is a lack of in-depth studies that explore the element distribution of KV cache to understand the hardness and limitation of KV cache quantization. To fill the gap, we conducted a comprehensive study on the element distribution in KV cache of popular LLMs. Our findings indicate that the key cache should be quantized per-channel, i.e., group elements along the channel dimension and quantize them together. In contrast, the value cache should be quantized per-token. From this analysis, we developed a tuning-free 2bit KV cache quantization algorithm, named KIVI. With the hardware-friendly implementation, KIVI can enable Llama (Llama-2), Falcon, and Mistral models to maintain almost the same quality while using 2.6× less peak memory usage (including the model weight). This reduction in memory usage enables up to 4× larger batch size, bringing 2.35× ∼ 3.47× throughput on real LLM inference workload. The source code is available at https://***/jy-yuan/KIVI. Copyright 2024 by the author(s)
The Sign Language Translation and Voice Impairment Support System (SLT-VISS) represents a groundbreaking application of deep learning methodology aimed at facilitating communication for individuals with hearing impair...
详细信息
Across all industries, cloud-based automated control systems have completely changed how operational and environmental parameters are tracked and controlled. With cloud-integrated systems for real-time data collection...
详细信息
Crop recommendation is the crucial aspect of modern agriculture, aiming to assist farmers in selecting the most suitable crops for their land and maximizing yield. In this study, the effectiveness of various preproces...
详细信息
A cloud-based Artificial Intelligence (AI) service has recently empowered the Internet of Medical Things (IoMT) in many applications on the remote Human Interaction Recognition of Pervasive Healthcare Monitoring (HIR-...
详细信息
暂无评论