Pavel

on the atlas — 31

• [2310.08586] PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm2 savers
• google maps - Google Search1 savers
• ReTransformer: ReRAM-based Processing-in-Memory Architecture for Transformer Acceleration | IEEE Conference Publication | IEEE Xplore1 savers
• ATT: A Fault-Tolerant ReRAM Accelerator for Attention-based Neural Networks | IEEE Conference Publication | IEEE Xplore1 savers
• Energon: Toward Efficient Acceleration of Transformers Using Dynamic Sparse Attention | IEEE Journals & Magazine | IEEE Xplore1 savers
• Sanger: A Co-Design Framework for Enabling Sparse Attention using Reconfigurable Architecture | MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture1 savers
• [2012.09852] SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning1 savers
• ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks | IEEE Conference Publication | IEEE Xplore1 savers
• [2002.10941] A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation1 savers
• Accelerating Transformer Networks through Recomposing Softmax Layers | IEEE Conference Publication | IEEE Xplore1 savers
• [2209.10797] DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation1 savers
• Hardware Accelerator for Multi-Head Attention and Position-Wise Feed-Forward in the Transformer | IEEE Conference Publication | IEEE Xplore1 savers
• [2007.08563] FTRANS: Energy-Efficient Acceleration of Transformers using FPGA1 savers
• MnnFast: A Fast and Scalable System Architecture for Memory-Augmented Neural Networks | IEEE Conference Publication | IEEE Xplore1 savers
• ls - Google Search1 savers
• TensorRT-LLM/examples/gemma/README.md at main · NVIDIA/TensorRT-LLM1 savers
• [2312.15159] Understanding the Potential of FPGA-Based Spatial Acceleration for Large Language Model Inference1 savers
• [2310.09949] Chameleon: a heterogeneous and disaggregated accelerator system for retrieval-augmented language models1 savers
• 4. Nsight Compute CLI — NsightCompute 12.4 documentation1 savers
• [2403.00579] NeuPIMs: NPU-PIM Heterogeneous Acceleration for Batched LLM Inferencing1 savers
• [2403.06664] Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System1 savers
• bloomberg - Google Search1 savers
• pica task llm - Google Search1 savers
• pip how to check version of package - Google Search1 savers
• [2304.07493] OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization1 savers
• Quantization and Hardware Architecture Co-Design for Matrix-Vector Multiplications of Large Language Models | IEEE Journals & Magazine | IEEE Xplore1 savers
• [2201.06618] VAQF: Fully Automatic Software-Hardware Co-Design Framework for Low-Bit Vision Transformer1 savers
• [2011.14203] EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference1 savers
• A Fast and Flexible FPGA-based Accelerator for Natural Language Processing Neural Networks | ACM Transactions on Architecture and Code Optimization1 savers
• [2401.11459] AttentionLego: An Open-Source Building Block For Spatially-Scalable Large Language Model Accelerator With Processing-In-Memory Technology1 savers
• [2401.11851] BETA: Binarized Energy-Efficient Transformer Accelerator at the Edge1 savers

highlights — 17

• Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System

  [2403.06664] Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System

• Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields

  Zip-NeRF

• SqueezeLLM: Dense-and-Sparse Quantization

  [2306.07629] SqueezeLLM: Dense-and-Sparse Quantization

• A Survey on Model Compression for Large Language Models

  [2308.07633] A Survey on Model Compression for Large Language Models

• GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

  [2005.03842] GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference

• Magic3D: High-Resolution Text-to-3D Content Creation

  [2211.10440] Magic3D: High-Resolution Text-to-3D Content Creation

• 3D Gaussian Splatting for Real-Time Radiance Field Rendering

  3D Gaussian Splatting for Real-Time Radiance Field Rendering

• GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

  [2311.11700] GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting

• GlueStick: Robust Image Matching by Sticking Points and Lines Together

  [2304.02008] GlueStick: Robust Image Matching by Sticking Points and Lines Together

• LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs

  [2206.10555] LargeKernel3D: Scaling up Kernels in 3D Sparse CNNs

• VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

  [1711.06396] VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection

• Photo-SLAM: Real-time Simultaneous Localization and Photorealistic Mapping for Monocular, Stereo, and RGB-D Cameras

  [2311.16728] Photo-SLAM: Real-time Simultaneous Localization and Photorealistic Mapping for Monocular, Stereo, and RGB-D Cameras

• Center-based 3D Object Detection and Tracking

  [2006.11275] Center-based 3D Object Detection and Tracking

• FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer

  [2301.08739] FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer

• PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm

  [2310.08586] PonderV2: Pave the Way for 3D Foundation Model with A Universal Pre-training Paradigm

• Point-NeRF: Point-based Neural Radiance Fields

  Point-NeRF: Point-based Neural Radiance Fields

• NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds

  NeuralEditor: Editing Neural Radiance Fields via Manipulating Point Clouds