Cover Image

ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Afifi, Salma, Thakkar, Ishan, Pasricha, Sudeep
Format:	Preprint
Published:	2024
Subjects:	Hardware Architecture Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SafeLight: Enhancing Security in Optical Convolutional Neural Network Accelerators
by: Afifi, Salma, et al.
Published: (2024)

Sustainable Transformer Neural Network Acceleration with Stochastic Photonic Computing
by: Afifi, S., et al.
Published: (2026)

PhotoGAN: Generative Adversarial Neural Network Acceleration with Silicon Photonics
by: Suresh, Tharini, et al.
Published: (2025)

Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics
by: Afifi, Salma, et al.
Published: (2024)

Accelerating Diffusion Models for Generative AI Applications with Silicon Photonics
by: Suresh, Tharini, et al.
Published: (2026)

Optical Computing for Deep Neural Network Acceleration: Foundations, Recent Developments, and Emerging Directions
by: Pasricha, Sudeep
Published: (2024)

OPIMA: Optical Processing-In-Memory for Convolutional Neural Network Acceleration
by: Sunny, Febin, et al.
Published: (2024)

CAFEEN: A Cooperative Approach for Energy Efficient NoCs with Multi-Agent Reinforcement Learning
by: Khan, Kamil, et al.
Published: (2024)

Silicon Photonic 2.5D Interposer Networks for Overcoming Communication Bottlenecks in Scale-out Machine Learning Hardware Accelerators
by: Sunny, Febin, et al.
Published: (2024)

An Analog and Digital Hybrid Attention Accelerator for Transformers with Charge-based In-memory Computing
by: Moradifirouzabadi, Ashkan, et al.
Published: (2024)

MixDiT: Accelerating Image Diffusion Transformer Inference with Mixed-Precision MX Quantization
by: Kim, Daeun, et al.
Published: (2025)

Graph Neural Networks Based Analog Circuit Link Prediction
by: Pan, Guanyuan, et al.
Published: (2025)

Scaling Analog Photonic Accelerators for Byte-Size, Integer General Matrix Multiply (GEMM) Kernels
by: Alo, Oluwaseun Adewunmi, et al.
Published: (2024)

RACE-IT: A Reconfigurable Analog Computing Engine for In-Memory Transformer Acceleration
by: Zhao, Lei, et al.
Published: (2023)

LLM-based AI Agent for Sizing of Analog and Mixed Signal Circuit
by: Liu, Chang, et al.
Published: (2025)

EEsizer: LLM-Based AI Agent for Sizing of Analog and Mixed Signal Circuit
by: Liu, Chang, et al.
Published: (2025)

A Runtime-Adaptive Transformer Neural Network Accelerator on FPGAs
by: Kabir, Ehsan, et al.
Published: (2024)

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization
by: Wu, Ka Wai
Published: (2024)

A Comparative Analysis of Microrings Based Incoherent Photonic GEMM Accelerators
by: Vatsavai, Sairam Sri, et al.
Published: (2024)

Efficient VQ-QAT and Mixed Vector/Linear quantized Neural Networks
by: Gou, Terry, et al.
Published: (2026)

AMPLE: Event-Driven Accelerator for Mixed-Precision Inference of Graph Neural Networks
by: Gimenes, Pedro, et al.
Published: (2025)

Algorithmic Strategies for Sustainable Reuse of Neural Network Accelerators with Permanent Faults
by: Alama, Youssef A. Ait, et al.
Published: (2024)

Layer-wise Weight Selection for Power-Efficient Neural Network Acceleration
by: Fang, Jiaxun, et al.
Published: (2025)

ZeroSim: Zero-Shot Analog Circuit Evaluation with Unified Transformer Embeddings
by: Yang, Xiaomeng, et al.
Published: (2025)

AnalogNAS-Bench: A NAS Benchmark for Analog In-Memory Computing
by: Bessalah, Aniss, et al.
Published: (2025)

SeVeDo: A Heterogeneous Transformer Accelerator for Low-Bit Inference via Hierarchical Group Quantization and SVD-Guided Mixed Precision
by: Choi, Yuseon, et al.
Published: (2025)

Exploring Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network Accelerators
by: Klhufek, Jan, et al.
Published: (2024)

AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
by: Gao, Jian, et al.
Published: (2025)

Scaling Photonic Tensor Cores with Unary and Homodyne Designs
by: Alo, Oluwaseun, et al.
Published: (2026)

Enhancing Reliability of Neural Networks at the Edge: Inverted Normalization with Stochastic Affine Transformations
by: Ahmed, Soyed Tuhin, et al.
Published: (2024)

HEANA: A Hybrid Time-Amplitude Analog Optical Accelerator with Flexible Dataflows for Energy-Efficient CNN Inference
by: Vatsavai, Sairam Sri, et al.
Published: (2024)

KirchhoffNet: A Scalable Ultra Fast Analog Neural Network
by: Gao, Zhengqi, et al.
Published: (2023)

MiCo: End-to-End Mixed Precision Neural Network Co-Exploration Framework for Edge AI
by: Jiang, Zijun, et al.
Published: (2025)

The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks
by: Yang, Chenghao, et al.
Published: (2022)

TreeLUT: An Efficient Alternative to Deep Neural Networks for Inference Acceleration Using Gradient Boosted Decision Trees
by: Khataei, Alireza, et al.
Published: (2025)

AnalogSAGE: Self-evolving Analog Design Multi-Agents with Stratified Memory and Grounded Experience
by: Wang, Zining, et al.
Published: (2025)

MCFlash: Bulk Bitwise Processing in 3D NAND with Dynamic Sensing and Multi-level Encoding
by: Rahman, Habib Ur, et al.
Published: (2026)

PiC-BNN: A 128-kbit 65 nm Processing-in-CAM-Based End-to-End Binary Neural Network Accelerator
by: Harary, Yuval, et al.
Published: (2026)

End-to-End Transformer Acceleration Through Processing-in-Memory Architectures
by: Yang, Xiaoxuan, et al.
Published: (2025)

ITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers
by: İslamoğlu, Gamze, et al.
Published: (2023)