cuBLASMp is well-suited to perform some of the most commonly used GEMMs in distributed machine learning. cuBLASMp 0.3.0 release added two such popular variants: AllGather+GEMM (AG+GEMM) and GEMM+ReduceScatter (G
assisted living,learning (artificial intelligence),pattern clustering,recurrent neural nets,software engineeringHuman activity recognition (HAR), driven by large deep learning models, has received a lot of attention in recent years due to its high applicability in diverse application domains, manipulate ...
SageMaker AI enables building, training, deploying machine learning models with managed infrastructure, tools, workflows. April 18, 2025 Sagemaker › dgBuilt-in algorithms and pretrained models in Amazon SageMaker SageMaker provides algorithms for supervised learning tasks like classification, regression, ...
In subject area:Computer Science Model parallelism refers to the technique of partitioning a machine learning model among multiple devices, where each device stores a portion of the model and processes data locally. This approach is used when the model is too large to fit on a single device, ...
In the message-passing programming model, tasks have private memories, and they communicate explicitly via message exchange. To exchange a message, each sends operation needs to have a corresponding receive operation. Tasks are not constrained to exist on the same physical machine. ...
Graph parallelism is widely used in many domains such as machine learning, data mining, physics, and electronic circuit design. Many problems in these domains can be modeled as graphs in which vertices represent computations and edges encode data dependencies or communications. Recall that a graph ...
deep-learningpytorchparallelismmodel-parallelismgpipepipeline-parallelismcheckpointing UpdatedJul 25, 2024 Python Create new JS processes for CPU intensive work react-nativethreadconcurrencyworkersweb-workerparallelism UpdatedJul 12, 2024 Java Parallel analytical database in pure Julia ...
Advances in Neural Information Processing Systems.虽然主要讨论卷积神经网络，但该论文中提到的并行训练...
machine-learningcompressiondeep-learninggpuinferencepytorchzerodata-parallelismmodel-parallelismmixture-of-expertspipeline-parallelismbillion-parameterstrillion-parameters UpdatedMar 29, 2025 Python kakaobrain/torchgpipe Star836 Code Issues Pull requests A GPipe implementation in PyTorch ...
State-of-the-art machine learning frameworks support a wide variety of design features to enable a flexible machine learning programming interface and to ease the programmability burden on machine learning developers. Identifying and using a performance-optimal setting in feature-rich frameworks, however...