Neural Network Hardware Acceleration

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63 papers20 papers in the last four weeks, up 300% on the four weeks before. 0.1% of all new papers.

  1. Atik: A Shared-Mesh Transformer Accelerator for RISC-V

    Nov 6, 2026Ahmed Zeer, Erkan UsluNeural Network Hardware AccelerationTransformer Inference

    Department of Computer Engineering Yildiz Technical University Istanbul, Turkiye

  2. Enabling Retraining-Free Accurate Inference in Analog Compute in Memory Accelerators

    Nov 5, 2026George Karfakis, Puneet GuptaCompute-in-MemoryNeural Network Hardware Acceleration

    Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, USA.

  3. CAMP: Context-Aware Mapping and Placement for LLMs on 3D-IMC Arrays

    Nov 5, 2026Orhun Görkem, Athanasios Vasilopoulos, Georgios Pagonis +6LLM Inference AccelerationAI Accelerator Inference

    IBM Research, Rüschlikon, Switzerland · IBM Research, San Jose, CA, USA

  4. Systolic Linear Attention: Co-Designing Tile-Grouped Gated Delta Attention for TPUs

    Nov 4, 2026Gagik Amirkhanyan, Nuojin ChengLinear AttentionAttention Mechanisms

    Google

  5. A Cross-Domain Matrix Engine for Signal Processing and Deep Neural Net Inference

    Nov 2, 2026Mehdi SafarpourNeural Network Hardware AccelerationEfficient Neural Network Inference

  6. FLAMIA: FLAsh MIcroscaling Attention for Fast and Causally Safe Training on Blackwell

    Nov 2, 2026Fedor Velikonivtsev, Mikhail Koltakov, Denis KuznedelevEfficient AttentionTransformer Attention

    Yandex Research

  7. Unlocking Turing Tensor Cores: A Measured Throughput Account of From-Scratch Pre-training on a Single 22G RTX 2080 Ti

    Nov 2, 2026Dezhou ShenNeural Network Hardware AccelerationGPU Acceleration

    Independent Researcher

  8. FlyWheel: Attention Kernels Built for the TPU

    Nov 1, 2026Zishuo Bao, Zeshen Zhang, Linkun Chen +1Neural Network Hardware AccelerationLLM Inference Acceleration

    New York University · New York University Shanghai · Google

  9. TADA: Technology Aware DNN Accelerator Performance and Energy Estimator

    Oct 30, 2026Tanvi Sharma, Surya Selvam, Anand Raghunathan +1Neural Network Hardware AccelerationEfficient Neural Network Inference

    Purdue University, West Lafayette, USA

  10. Input-dependent Neuromodulation Enhances Mixed-Signal Neuromorphic Hardware

    Oct 30, 2026Aashman Mehta, AbdelQader AlKilany, Dan F. M. Goodman +2Neuromorphic ComputingSpiking Neural Networks

    Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland · University of California, Los Angeles, CA, USA · Imperial College London, London, UK

  11. Hardware-Aware Model Inversion in Memristive Spiking Neural Networks

    Oct 29, 2026Pablo Sorrentino, Fernando M. Quintana, Erika Covi +1Model Inversion AttacksSpiking Neural Networks

    University of Groningen, Groningen, The Netherlands · Technical University of Munich, Munich, Germany.

  12. MulClip: A table-free activation function with monotonic and folding regimes for reservoir computing on microcontrollers

    Oct 29, 2026Guren Matsumura, Masato Takemoto, Shinzo KoyamaNeural Network Activation FunctionsReservoir Computing

    Panasonic Industry Co., Ltd., Osaka, Japan

  13. SpikeAD: Toward Multiplication-Free Spike-Controlled Neuromorphic Architecture for Energy-Efficient Small Object Detection

    Oct 28, 2026Zhifan Song, Haralampos-G. StratigopoulosEfficient Object DetectionSpiking Neural Networks

    Sorbonne University, CNRS, LIP6, Paris, France

  14. Hardware-Matched Spiking Neural Networks for Real-Time Purkinje Cell Spike Classification

    Oct 27, 2026Arooba Farhan, Afsah Syed, Muhammad Fahd Ibrahim Bhatti +4Spiking Neural NetworksEfficient Neural Network Inference

    Electrical Engineering Department, Lahore University of Management Sciences, Pakistan · Department of Neuroscience, Erasmus University Medical Center, Rotterdam, The Netherlands

  15. ChroNoC: A Tableless TDM Circuit-Switched NoC With Delay-Aware Deployment for Time-Sensitive Neuromorphic Computing

    Oct 25, 2026Mohammad Rasoul Roshanshah, Mehdi Modarressi, Saeed SafariNeuromorphic ComputingNeural Network Hardware Acceleration

    The authors are with the School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

  16. Adapting DNNs to Embrace Voltage Scaling Induced Errors via Accumulation-Aware Quantization

    Oct 24, 2026Alexis Maras, Panagiotis Chaidos, Georgios Alexandris +2Neural Network Hardware AccelerationHardware-Aware Quantization

    National Technical University of Athens, Athens, Greece

  17. Every Weight Is a Path of Shared Discrete Decisions

    Oct 22, 2026Ammar Ali, Stamatis LefkimmiatisNeural Network CompressionNeural Network Hardware Acceleration

    LEAD Lab, ITMO University

  18. Decode Late, Multiply Once: Rethinking the Dot Product for Quantized Weights

    Oct 22, 2026Jonathan TapsonNeural Network Hardware AccelerationLow-Bit Quantization

    BrainChip Inc, Laguna Hills, CA, USA

  19. CANNBot-CAKE: Collaborative Agentic Kernel Evolution for Ascend NPU

    Oct 22, 2026Deng Pan, Xue-Jian Gao, Junyi Fan +8Agentic Code GenerationNeural Network Hardware Acceleration

    Huawei

  20. TernScope: Model-Hardware Co-Design for Efficient Ternary Endoscopic Segmentation

    Oct 21, 2026Zhuoyu Wu, Wenhui Ou, Qiawei Zheng +3Medical Image SegmentationNeural Network Hardware Acceleration

    CyPhi AI Research Lab, School of Information Technology, Monash University Malaysia, Malaysia · Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong · School of Computer Science and Engineering, Southeast University, Nanjing, China +1

  21. TrainBridge: Agentic NPU Training Optimization Guided by GPU Compilation Evidence

    Oct 21, 2026Yupeng Chen, Kunxiang Zhao, Xingjian Wang +6Neural Network Hardware Acceleration

    Shenzhen Loop Area Institute · The Chinese University of Hong Kong, Shenzhen, China · Autokernel

  22. 3D-MoE: Complementarity-Guided Hardware-Software Co-Design for MoE Decode on 3D-Stacked NMP

    Oct 19, 2026Yudong Pan, Lian Liu, Shixin Zhao +8Neural Network Hardware AccelerationMixture-of-Experts Inference

    SKLP, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China · University of Edinburgh, Edinburgh, United Kingdom

  23. Small-scale neural simulation of Caenorhabditis elegans on Loihi-2 using NeuroML2Loihi

    Oct 18, 2026Danny Rosen, Ramashish Gaurav, Yang YiNeuromorphic ComputingNeural Network Hardware Acceleration

    Virginia Tech, Institute for Advanced Computing

  24. First-Order LoRA Training with Phone NPUs

    Oct 17, 2026Xu Zheng, Wei Cheng, Zhuomin Chen +4On-Device Language Model Fine-TuningOn-Device Training

    Florida International University, Miami, FL, USA · NEC Laboratories America, Princeton, NJ, USA · North Carolina State University, Raleigh, NC, USA +2

  25. TorchTPU - A Hybrid Eager/Compiled Architecture for Native PyTorch Execution on TPU

    Oct 16, 2026Claudio Basile, Michael Voznesensky, Gunhyun Park +50Neural Network Hardware AccelerationEfficient Neural Network Inference

  26. qGAMMA: A Framework for Optimal DNN Mapping on Multi-Precision Accelerators

    Oct 16, 2026Leandro Fiorin, Luigi Altamura, Cristina SilvanoNeural Network Hardware Acceleration

    Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy. · Department of Computer Science and Engineering, Chalmers University of Technology and University of Gothenburg, SE-41296 Gothenburg, Sweden

  27. Hardware-aware Calibrated Clustered Attention for Efficient Visual Geometric Transformers

    Oct 7, 2026Weitian Wang, Shubham Rai, Cecilia De La Parra +1Neural Network Hardware AccelerationEfficient ViTs

    Robert Bosch GmbH, Germany · Ruhr University Bochum, Germany

  28. Beyond Masked Sparsity: SNACK Enables Truly Sparse Neural Networks on GPU

    Oct 2, 2026Jafar Badour, Maurice van Keulen, Elena MocanuDynamic Sparse TrainingSparse Neural Networks

    University of Twente

  29. LampAttention: Look-Ahead Mixed-Precision FlashAttention for Dedicated Accelerators

    Sep 30, 2026Stanislav Budzinskiy, Marian Gloser, Tolunay Yilmaz +5AI Accelerator InferenceLLM Inference Acceleration

    Faculty of Mathematics University of Vienna, Austria · Huawei Heisenberg Research Center, Munich, Germany · Huawei Technologies Co. Ltd

  30. KernelOPT: Dispatch-Aware Agentic Search for GPU Kernel Optimization

    Sep 24, 2026Aheli Poddar, Sanskar Prasad, Arindam Samanta +3GPU Kernel OptimizationAgentic Search

    Red Hat