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GPUVM: GPU-driven Unified Virtual Memory

Nurlan Nazaraliyev, Elaheh Sadredini, Nael Abu-Ghazaleh

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Tags: Computer science, CUDA, Memory, nVidia, Operating systems, Performance, Tesla V100

November 17, 2024 by hgpu

NEO: Saving GPU Memory Crisis with CPU Offloading for Online LLM Inference

Xuanlin Jiang, Yang Zhou, Shiyi Cao, Ion Stoica, Minlan Yu

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Tags: Artificial intelligence, Computer science, CUDA, LLM, Memory, nVidia, nVidia A10, nVidia H100, Tesla T4

November 10, 2024 by hgpu

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

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Gabin Schieffer, Ruimin Shi, Stefano Markidis, Andreas Herten, Jennifer Faj, Ivy Peng

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Tags: AMD, AMD Radeon Instinct MI250X, ATI, Computer science, HIP, Machine learning, Memory, Performance

October 6, 2024 by hgpu

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Gabin Schieffer, Jacob Wahlgren, Jie Ren, Jennifer Faj, Ivy Peng

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Tags: Computer science, CUDA, HPC, Memory, nVidia, nVidia H100, Performance, Quantum computing

July 14, 2024 by hgpu

Towards Unified Analysis of GPU Consistency

Haining Tong, Natalia Gavrilenko, Hernán Ponce de León, Keijo Heljanko

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Tags: Computer science, Memory, nVidia, OpenCL, Package, PTX, Vulkan

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

Gallatin: A General-Purpose GPU Memory Manager

Hunter McCoy, Prashant Pandey

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Tags: Computer science, CUDA, HPC, Memory, nVidia, nVidia A40, Package

February 4, 2024 by hgpu

Unified Shared Memory: Friend or Foe?

Juan Fumero Alfonso, Florin-Gabriel Blanaru, Athanasios Stratikopoulos, Steve Dohrmann, Sandhya Viswanathan, Christos-Efthymios Kotselidis

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Tags: Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, Java, Memory, nVidia, nVidia GeForce RTX 3070, OpenCL

September 17, 2023 by hgpu

GGArray: A Dynamically Growable GPU Array

Enzo meneses, Cristóbal A. Navarro, Héctor Ferrada

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Tags: Algorithms, Computer science, CUDA, Memory, nVidia, nVidia A100, nVidia Titan RTX

September 4, 2022 by hgpu

Memory Optimization for Deep Networks

Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl

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Tags: Computer science, CUDA, Deep learning, Memory, nVidia, Optimization, Package, PyTorch, Tesla P100

November 1, 2020 by hgpu

Bounds Checking on GPU

Troels Henriksen

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance

August 2, 2020 by hgpu

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

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high performance computing on graphics processing units: hgpu.org

GPUVM: GPU-driven Unified Virtual Memory

NEO: Saving GPU Memory Crisis with CPU Offloading for Online LLM Inference

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

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Harnessing Integrated CPU-GPU System Memory for HPC: a first look into Grace Hopper

Towards Unified Analysis of GPU Consistency

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

Gallatin: A General-Purpose GPU Memory Manager

Unified Shared Memory: Friend or Foe?

GGArray: A Dynamically Growable GPU Array

Memory Optimization for Deep Networks

Bounds Checking on GPU

Recent source codes

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

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