Search Results for author: Jeff Johnson

Found 8 papers, 5 papers with code

The Faiss library

1 code implementation16 Jan 2024 Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, Hervé Jégou

The Faiss library is dedicated to vector similarity search, a core functionality of vector databases.

Generative AI Beyond LLMs: System Implications of Multi-Modal Generation

no code implementations22 Dec 2023 Alicia Golden, Samuel Hsia, Fei Sun, Bilge Acun, Basil Hosmer, Yejin Lee, Zachary DeVito, Jeff Johnson, Gu-Yeon Wei, David Brooks, Carole-Jean Wu

As the development of large-scale Generative AI models evolve beyond text (1D) generation to include image (2D) and video (3D) generation, processing spatial and temporal information presents unique challenges to quality, performance, and efficiency.

3D Generation

GPU-based Private Information Retrieval for On-Device Machine Learning Inference

1 code implementation26 Jan 2023 Maximilian Lam, Jeff Johnson, Wenjie Xiong, Kiwan Maeng, Udit Gupta, Yang Li, Liangzhen Lai, Ilias Leontiadis, Minsoo Rhu, Hsien-Hsin S. Lee, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, G. Edward Suh

Together, for various on-device ML applications such as recommendation and language modeling, our system on a single V100 GPU can serve up to $100, 000$ queries per second -- a $>100 \times$ throughput improvement over a CPU-based baseline -- while maintaining model accuracy.

Information Retrieval Language Modelling +1

Improving the Effectiveness of Traceability Link Recovery using Hierarchical Bayesian Networks

no code implementations18 May 2020 Kevin Moran, David N. Palacio, Carlos Bernal-Cárdenas, Daniel McCrystal, Denys Poshyvanyk, Chris Shenefiel, Jeff Johnson

To this end, we design and implement a HierarchiCal PrObabilistic Model for SoftwarE Traceability (Comet) that is able to infer candidate trace links.

Rethinking floating point for deep learning

1 code implementation1 Nov 2018 Jeff Johnson

In 16 bits, our log float multiply-add is 0. 59x the power and 0. 68x the area of IEEE 754 float16 fused multiply-add, maintaining the same signficand precision and dynamic range, proving useful for training ASICs as well.

Math Quantization

An evaluation of large-scale methods for image instance and class discovery

no code implementations9 Aug 2017 Matthijs Douze, Hervé Jégou, Jeff Johnson

While k-means is usually considered as the gold standard for this task, we evaluate and show the interest of diffusion methods that have been neglected by the state of the art, such as the Markov Clustering algorithm.

Clustering Instance Search

Billion-scale similarity search with GPUs

12 code implementations28 Feb 2017 Jeff Johnson, Matthijs Douze, Hervé Jégou

Similarity search finds application in specialized database systems handling complex data such as images or videos, which are typically represented by high-dimensional features and require specific indexing structures.

Image Similarity Search Quantization

Fast Convolutional Nets With fbfft: A GPU Performance Evaluation

2 code implementations24 Dec 2014 Nicolas Vasilache, Jeff Johnson, Michael Mathieu, Soumith Chintala, Serkan Piantino, Yann Lecun

We examine the performance profile of Convolutional Neural Network training on the current generation of NVIDIA Graphics Processing Units.

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