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The New Compiler Stack: A Survey on the Synergy of LLMs and Compilers

Shuoming Zhang, Jiacheng Zhao, Qiuchu Yu, Chunwei Xia, Zheng Wang, Xiaobing Feng, Huimin Cui

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Tags: Artificial intelligence, Compilers, Computer science, LLM, Programming Languages, Software Engineering

January 12, 2026 by hgpu

Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs

Rupanshu Soi, Rohan Yadav, Fredrik Kjolstad, Alex Aiken, Maryam Mehri Dehnavi, Michael Garland, Michael Bauer

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Tags: Computer science, CUDA, nVidia, nVidia B200, nVidia H100, Programming Languages

December 29, 2025 by hgpu

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Yaoyao Ding, Bohan Hou, Xiao Zhang, Allan Lin, Tianqi Chen, Cody Hao Yu, Yida Wang, Gennady Pekhimenko

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Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia H100, nVidia L40s, Package, Programming Languages, PTX, Triton

December 29, 2025 by hgpu

The Anatomy of a Triton Attention Kernel

Burkhard Ringlein, Jan van Lunteren, Radu Stoica, Thomas Parnell

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Tags: AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, ATI, Computer science, CUDA, DSL, HIP, LLM, nVidia, nVidia H100, Performance, Programming Languages, Triton

November 23, 2025 by hgpu

Dato: A Task-Based Programming Model for Dataflow Accelerators

Shihan Fang, Hongzheng Chen, Niansong Zhang, Jiajie Li, Han Meng, Adrian Liu, Zhiru Zhang

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Tags: Computer science, FPGA, nVidia, Package, Programming Languages, Python

September 21, 2025 by hgpu

CrossTL: A Universal Programming Language Translator with Unified Intermediate Representation

Nripesh Niketan, Vaatsalya Shrivastva

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Tags: Compilers, Computer science, CUDA, DirectX, GLSL, HIP, HLSL, nVidia, OpenGL, Package, Programming Languages, Vulkan

September 7, 2025 by hgpu

NPUEval: Optimizing NPU Kernels with LLMs and Open Source Compilers

Sarunas Kalade, Graham Schelle

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Tags: Code generation, Computer science, Machine learning, Programming Languages

August 3, 2025 by hgpu

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

Hossein Albakri, Kazem Cheshmi

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Tags: Compilers, Computer science, CUBLAS, CUDA, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia A100, Programming Languages, Sparse matrix

June 22, 2025 by hgpu

GPUMC: A Stateless Model Checker for GPU Weak Memory Concurrency

Soham Chakraborty, S. Krishna, Andreas Pavlogiannis, Omkar Tuppe

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, OpenCL, Programming Languages

June 8, 2025 by hgpu

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Ahmed Heakl, Sarim Hashmi, Gustavo Bertolo Stahl, Seung Hun Eddie Han, Salman Khan, Abdulrahman Mahmoud

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Tags: AI, AMD Radeon RX 7900 XT, ATI, Computer science, CUDA, HIP, Machine learning, nVidia, nVidia A100, OpenCL, Package, Programming Languages, PTX

May 25, 2025 by hgpu

Comparing Parallel Functional Array Languages: Programming and Performance

David van Balen, Tiziano De Matteis, Clemens Grelck, Troels Henriksen, Aaron W. Hsu, Gabriele K. Keller, Thomas Koopman, Trevor L. McDonell, Cosmin Oancea, Sven-Bodo Scholz, Artjoms Sinkarovs, Tom Smeding, Phil Trinder, Ivo Gabe de Wolff, Alexandros Nikolaos Ziogas

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Tags: Benchmarking, Computer science, CUDA, HIP, N-body simulation, nVidia, nVidia A30, OpenCL, Package, Performance, performance portability, Programming Languages

May 18, 2025 by hgpu

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

Michele Martone, Julia Lawall

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Tags: Computer science, CUDA, HIP, HPC, nVidia, OpenMP, Package, Programming Languages

March 30, 2025 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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