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Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Reza Abbasi, Sernam Lim

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Tags: AI, Artificial intelligence, Computer science, CUDA, LLM, Machine learning, Memory, nVidia, nVidia GeForce RTX 3090, nVidia Quadro RTX 8000, Package

October 20, 2024 by hgpu

Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores

Shaobo Ma, Chao Fang, Haikuo Shao, Zhongfeng Wang

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Tags: Computer science, CUDA, Data recovery, Extended precision, LLM, Matrix multiplication, nVidia, nVidia GeForce RTX 3090, Security

October 6, 2024 by hgpu

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Marek Palkowski, Mateusz Gruzewski

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Tags: AMD Radeon RX 6800, ATI, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenCL, OpenMP

September 29, 2024 by hgpu

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

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Tags: AI, Computer science, CUDA, LLM, Machine learning, NLP, nVidia, nVidia A800

July 28, 2024 by hgpu

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

Kangwei Xu, Grace Li Zhang, Xunzhao Yin, Cheng Zhuo, Ulf Schlichtmann, Bing Li

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Tags: Code generation, Computer science, FPGA, HLS, LLM

July 14, 2024 by hgpu

Chat AI: A Seamless Slurm-Native Solution for HPC-Based Services

Ali Doosthosseini, Jonathan Decker, Hendrik Nolte, Julian M. Kunkel

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Tags: AI, Cloud, Computer science, HPC, LLM, nVidia, nVidia H100, Package, PC cluster

July 7, 2024 by hgpu

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

Avinash Maurya, Jie Ye, M. Mustafa Rafique, Franck Cappello, Bogdan Nicolae

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Tags: Computer science, CUDA, LLM, Memory, nVidia, nVidia A100, nVidia H100, Performance

June 23, 2024 by hgpu

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

UVaFTLE: Lagrangian finite time Lyapunov exponent extraction for fluid dynamic applications

Challenging Portability Paradigms: FPGA Acceleration Using SYCL and OpenCL

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high performance computing on graphics processing units: hgpu.org

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Efficient Arbitrary Precision Acceleration for Large Language Models on GPU Tensor Cores

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers

Recent source codes

EnergyUCB-Bandit

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

MFC: Exascale simulation of multiphase/physics fluid dynamics

UVaFTLE: Lagrangian finite time Lyapunov exponent extraction for fluid dynamic applications

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