Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

Scaling distributed SQL queries needs more performance and efficiency in the agentic AI era. It’s a challenge Cockroach is looking to solve.

In this article, I'll show how a distributed, in-memory data grid with an integrated compute engine can enable applications to run familiar TPL-based, data-parallel applications on a cluster of ...

In these architectures, data is distributed across several specialized data stores ... pushing down as much processing as possible to the data sources. 2. Using parallel in-memory computation to ...

This makes it possible to implement certain training methods for ML models such as Distributed Data Parallel (DDP), in which only one model replica is executed per high-speed accelerator area and ...

followed by distributed training at scale using PyTorch with Distributed Data Parallel (DDP) and TensorFlow with Horovod, all driven by the oneCCL communication library. Additionally, the speakers ...

In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the ...

“Distributed-data-parallel and fully-sharded-data-parallel techniques for model replication and data partitioning allow for the best system utilization and model performance.” Identifying data ...