A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Felix Gremse, Marius Stärk, Josef Ehling, et al.
A GPU-accelerated software tool for interactive segmentation and rendering of multimodal biomedical volume data.
Norman P. Jouppi, Cliff Young, Nishant Patil, et al.
Evaluates a custom ASIC (TPU) for neural network inference, showing 15-30x speedup and 30-80x TOPS/Watt over contemporary CPUs and GPUs.
Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton
AlexNet achieved state-of-the-art image classification on ImageNet using a deep CNN with 60M parameters, ReLU, GPU training, and dropout.
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QLoRA enables fine-tuning of large language models on a single GPU by combining 4-bit NormalFloat quantization, double quantization, and paged optimizers, matching 16-bit performance.
Junsong Chen, Jincheng Yu, Yitong Li, et al.
SANA-Video 2.0 introduces hybrid linear-softmax attention and attention residuals to achieve softmax-level video quality with linear-complexity scaling, enabling 720p generation on a single GPU.
Hongzheng Chen, Jiahao Zhang, Yixiao Du, et al.
This paper investigates FPGA-based spatial acceleration for LLM inference, achieving up to 13.4x speedup over prior FPGA accelerators and 5.7x energy efficiency vs. A100 GPU.
Zhisheng Ye, Wei Gao, Qinghao Hu, et al.
A survey of deep learning workload scheduling in GPU datacenters, covering training and inference, objectives, resource utilization, and future directions.