GPU Kernel Optimization

GPU: Graphics Processing Unit

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14 papers in the last four weeks, up 75% on the four weeks before. 0.1% of all new papers.

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Local-GS: Accelerating 3D Gaussian Splatting via Tile-Local Warp Coherence
Jun 15, 2026Yang Luo, Yan Gong, Yongsheng Gao +33D Gaussian Splatting 3DGS Acceleration
State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, the School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China · Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization
Jun 15, 2026Dayuan Fu, Mohan Jiang, Tongyu Wang +5RL for Code Generation GPU Kernel Optimization
1SII · 2SJTU · 3GAIR
From Tokens to Regions: CUDA-Sensitive Instruction Tuning for GPU Kernel Generation
Jun 15, 2026Wentao Chen, Jiace Zhu, Xing Zhe Chai +4GPU Kernel Optimization LLM Fine-Tuning
1Shanghai Jiao Tong University · 2Biren Technology
Accelerating GPU Inference of Large Language Models with Moderately Unstructured Sparse Weight Matrices
Jun 13, 2026Tao Lu, Haoyu Wang, Zonghui Wang +3LLM Pruning GPU Kernel Optimization
National University of Singapore · Zhejiang University
Realizing Native INT8 Compute for Diffusion Transformers on Consumer GPUs: A Fused INT8 GEMM Kernel for Ideogram 4.0
Jun 12, 2026Ali Asaria, Tony Salomone, Deep GandhiGPU Kernel Optimization Diffusion Transformer
Transformer Lab
MiniMax Sparse Attention
Jun 11, 2026Xunhao Lai, Weiqi Xu, Yufeng Yang +14GPU Kernel Optimization Long-Context Language Modeling
MiniMax · Peking University · NVIDIA +4
ReSET: Accurate Latency-Critical NVFP4 Reasoning via Step-Aware Temperature Scaling
Jun 11, 2026Sihwa Lee, Janghwan Lee, Donghoon Yoo +4LLM Quantization Language Model Decoding
Hanyang University, Seoul, Republic of Korea · Xenoscube Korean Inc., Seoul, Republic of Korea
Performance Analysis and Optimization of 3D Generative Diffusion Models across GPU Architectures
Jun 11, 2026Jeeho Ryoo, Yongchan Jung, Muhammad Ali Khaliq +3Medical Imaging GPU Kernel Optimization
Fairleigh Dickinson University Vancouver, BC, Canada · The University of Colorado at Colorado Springs Colorado Springs, CO, USA · Northeastern University Vancouver, BC, Canada
Rigel: Reverse-Engineering the Metal 4.1 Tensor Compute Path on the Apple M4 Max GPU
Jun 11, 2026Ramchand KumaresanGPU Kernel Optimization GPU Acceleration
Murai Labs
Flash-GMM: A Memory-Efficient Kernel for Scalable Soft Clustering
Jun 9, 2026Gal Bloch, Ariel Gera, Matan Orbach +2GPU Kernel Optimization GPU Acceleration
IBM Research
AutoMegaKernel: A Statically-Checked Agent Harness for Self-Retargeting Megakernel Synthesis
Jun 8, 2026Jaber Jaber, Osama JaberGPU Kernel Optimization High-Performance Computing
RightNow AI
Toward Compiler World Models: Learning Latent Dynamics for Efficient Tensor Program Search
Jun 8, 2026Haolin Pan, Lianghong Huang, Xvlin Zhou +2GPU Kernel Optimization Latent World Models
Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, China · Institute of Software, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China
Resource-aware Computation-Communication Overlap for multi-GPU ML Workloads
Jun 8, 2026Minyu Cui, Miquel PericasGPU Kernel Optimization Communication-Efficient Distributed Training
Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
APEX4: Efficient Pure W4A4 LLM Inference via Intra-SM Compute Rebalancing
Jun 7, 2026Hong Guo, Nianhui Guo, Weixing Wang +3LLM Quantization GPU Kernel Optimization
Hasso Plattner Institute · German University of Digital Science
Attention at the Theoretical Minimum: A Mathematics of Arrays Framework for Memory-Optimal Transformer Kernels
Jun 5, 2026Lenore Mullin, Gaetan HainsGPU Kernel Optimization Energy-Efficient ML
University at Albany, SUNY, Albany, NY, USA · LACL, Université Paris-Est Créteil, Créteil, France
MusaCoder: Native GPU Kernel Generation with Full-Stack Training on Moore Threads GPU
Jun 3, 2026Kun Cheng, Songshuo Lu, Sicong Liao +7RL for Code Generation GPU Kernel Optimization
Moore Threads AI
KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators
Jun 1, 2026Taras Sereda, Burak Bartan, Ankita Nayak +3AI Accelerator Inference GPU Kernel Optimization
Gimlet Labs Inc., San Francisco, California, USA
Scaling Parallel Sequence Models to Foundation-Scale Vision Encoders
May 30, 2026Yitong Jiang, Hongjun Wang, Collin McCarthy +15GPU Kernel Optimization Vision Foundation Models
NVIDIA · The Chinese University of Hong Kong · The University of Hong Kong +1
On Efficient Scaling of GNNs via IO-Aware Layers Implementations
May 29, 2026Daria Fomina, Daniil Krasylnikov, Alexey Boykov +3Graph Attention Networks GPU Kernel Optimization
1Yandex · 2HSE University · 3ITMO University
GPU Forecasters: Language Models as Selective Surrogates for Kernel Runtime Optimization
May 29, 2026Zaid Khan, Justin Chih-Yao Chen, Jaemin Cho +2Neural Surrogate Modeling GPU Kernel Optimization
UNC Chapel Hill · AI2 · Johns Hopkins University +1
Reducing the GPU Memory Bottleneck with Lossless Compression for ML -- Extended
May 29, 2026Aditya K Kamath, Arvind Krishnamurthy, Marco Canini +1Efficient Neural Network Inference GPU Kernel Optimization
University of Washington Seattle, WA, USA · KAUST Thuwal, Saudi Arabia
Caspar: CUDA Accelerator for Symbolic Programming with Adaptive Reordering
May 28, 2026Emil Martens, Aaron Miller, Matias Varnum +1Bundle Adjustment GPU Kernel Optimization
Norwegian University of Science and Technology · Skydio
Memory-Bound but Not Bandwidth-Limited: The Physical AI Inference Gap in Batch-1 LLM Decode
May 28, 2026Josef ChenGPU Kernel Optimization GPU Acceleration
KAIKAKU
HTAM: Hierarchical Transition-Attended Memory for Operator Optimization
May 28, 2026Yining Zhang, Mingyang Yi, Chen Wang +5GPU Kernel Optimization Memory-Augmented Language Models
School of Artificial Intelligence, University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences · Zhongguancun Academy +1
KLineage: Recovering the Missing When of Kernel Optimization by Deoptimizing Experts
May 27, 2026Shuoming Zhang, Qiuchu Yu, Ruiyuan Xu +11GPU Kernel Optimization GPU Acceleration
SKLP, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences · University of New South Wales
Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation
May 26, 2026Yee Hin Chong, Jiaming Wu, Youhui Zhang +1GPU Kernel Optimization LLM Agent Evaluation
Department of Computer Science and Technology, Tsinghua University, Beijing, China · Beijing National Research Center for Information Science and Technology, Beijing, China
Step-TP: A Grounded, Step-Level Dataset with Chain-of-Thought Reasoning for LLM-Guided Tensor Program Optimization
May 25, 2026Mengfan Liu, Da Zheng, Junwei Su +1GPU Kernel Optimization Large Language Model-Guided Optimization
The University of Hong Kong Hong Kong, China · Ant Group Hangzhou, China · University of Science and Technology of China Hefei, China
FastKernels: Benchmarking GPU Kernel Generation in Production
May 22, 2026Gabriele Oliaro, Yichao Fu, May Jiang +5GPU Kernel Optimization GPU Acceleration
1Snowflake AI Research · 2CMU · 3UCSD +1
From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$ -Sparse GLMs
May 21, 2026Jiachang Liu, Andrea LodiBranch and Bound GPU Kernel Optimization
∗Center for Data Science for Enterprise and Society, Cornell University, Ithaca, USA · †School of Operations Research and Information Engineering, Cornell University, Ithaca, USA · ‡Jacobs Technion-Cornell Institute, Cornell Tech and Technion–IIT, New York, USA
Prior Knowledge or Search? A Study of LLM Agents in Hardware-Aware Code Optimization
May 19, 2026Dmitry Redko, Albert Fazlyev, Konstantin Sozykin +3GPU Kernel Optimization Large Language Model-Guided Optimization
Applied AI Institute · AI Talent Hub, ITMO University · YSDA +1

Jun 15, 2026, cs.CVJ/K move · Enter open · S save

Local-GS: Accelerating 3D Gaussian Splatting via Tile-Local Warp Coherence

Yang Luo, Yan Gong, Yongsheng Gao, Jie Zhao+2

State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China · State Key Laboratory of Intelligent Green Vehicle and Mobility, the School of Vehicle and Mobility, Tsinghua University, Beijing 100084, China · Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

3D Gaussian Splatting 3DGS Acceleration GPU Kernel Optimization GPU Acceleration

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3D Gaussian Splatting (3DGS) has significantly advanced real-time novel view synthesis by representing scenes as dense collections of anisotropic 3D Gaussian primitives. However, the irregular spatial distribution of Gaussians often leads to poor GPU utilization, as warp divergence and redundant computation degrade rendering performance. To address this, we present Local-GS, a warp-coherent rendering paradigm that, organizes Gaussian primitives with respect to SIMT (Single Instruction, Multiple Threads) execution boundaries rather than scene geometry. Specifically, we propose three warp-coherent stages: a hoisting stage that precomputes shared parameters at tile level, a culling stage that discards warps with no contribution, and a blending stage that replaces per-pixel branching with a uniform instruction stream. Across extensive benchmarks on multiple datasets, Local-GS improves efficiency without compromising quality. As a plug-and-play optimization, it provides additional performance gains to all tested baselines, culminating in a

7.76\times

speedup on Deep Blending scenes.

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Latest papers 126