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Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Francesco Barchi, Emanuele Parisi, Andrea Bartolini, Andrea Acquaviva

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Optimization, Overview, Security

August 7, 2022 by hgpu

Real-Time High-Performance Computing for Embedded Control Systems

Alejandro Josué Calderón Torres

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Tags: Code generation, Computer science, Embedded high-performance computing, nVidia, nVidia Jetson AGX Xavier, nVidia Jetson Nano, nVidia Jetson TX2, OpenCL, Tesla T4, Tesla V100, Thesis

August 7, 2022 by hgpu

COX: Exposing CUDA Warp-Level Functions to CPUs

Ruobing Han, Jaewon Lee, Jaewoong Sim, Hyesoon Kim

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Tags: Benchmarking, Compilers, Computer science, CUDA, HIP, nVidia

August 7, 2022 by hgpu

Design and Implementation of ShenWei Universal C/C++

Huanqi Cao, Jiajie Chen

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Tags: Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL

August 7, 2022 by hgpu

Demystifying Dependency Bugs in Deep Learning Stack

Kaifeng Huang, Bihuan Chen, Susheng Wu, Junmin Cao, Lei Ma, Xin Peng

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia

July 24, 2022 by hgpu

CPU-GPU Layer-Switched Low Latency CNN Inference

Ehsan Aghapour, Dolly Sapra, Andy Pimentel, and Anuj Pathania

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Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL, Package, SoC

July 24, 2022 by hgpu

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

María Ángelica Dávila Gúzman

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Tags: Computer science, FPGA, HLS, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

July 24, 2022 by hgpu

Theseus: A Library for Differentiable Nonlinear Optimization

Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky Chen, Joseph Ortiz, Daniel DeTone, Austin Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam

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Tags: Computer science, CUDA, Deep learning, Nonlinear optimization, nVidia, Package, Tesla V100

July 24, 2022 by hgpu

On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention

Menglu Yu, Bo Ji, Hridesh Rajan, Jia Liu

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Tags: Computer science, Deep learning, GPU cluster, Task scheduling

July 24, 2022 by hgpu

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Philip Jon Børgesen

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Performance, Thesis

July 17, 2022 by hgpu

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava

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Tags: Computer science, Heterogeneous systems, IoT, Machine learning, nVidia, nVidia GeForce GTX 760, nVidia GeForce GTX 860, OpenCL

July 17, 2022 by hgpu

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Shilei Tian, Joseph Huber, Barbara Chapman, Johannes Doerfert

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Tags: AMD Radeon Instinct MI100, ATI, Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, OpenMP

July 17, 2022 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

Applications

Deep Learning Approaches to Source Code Analysis for Optimization of Heterogeneous Systems: Recent Results, Challenges and Opportunities

Real-Time High-Performance Computing for Embedded Control Systems

COX: Exposing CUDA Warp-Level Functions to CPUs

Design and Implementation of ShenWei Universal C/C++

Demystifying Dependency Bugs in Deep Learning Stack

CPU-GPU Layer-Switched Low Latency CNN Inference

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

Theseus: A Library for Differentiable Nonlinear Optimization

On Scheduling Ring-All-Reduce Learning Jobs in Multi-Tenant GPU Clusters with Communication Contention

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

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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