It was only a few months ago when waferscale compute pioneer Cerebras Systems was bragging that a handful of its WSE-3 ...

We used a combination of data parallelism, tensor parallelism, sequence parallelism, and Fully Sharded Data Parallel (FSDP) to scale training along multiple dimensions such as data, model, and ...

Tensor parallelism is employed within each machine due to high bandwidth, while pipeline parallelism is used across machines to manage lower inter-machine connectivity. Micro-batching further ...

Parallel structure is used in sentences to promote readability as well as to create a common level of importance between ideas. Also know as parallelism, using parallel structure creates a common ...

作者 | PPIO 算法专家张青青前   言近一年以来，自 H2O 起，关于 KV 稀疏的论文便百花齐放，而在实际应用中不得不面临的一个问题便是学术论文与实际应用之间的巨大鸿沟，例如，像 vLLM 等框架采用的是 PagedAttention ...

Training is conducted using a combination of tensor, fully-sharded-data-parallel, and sequence parallelism, allowing training to scale to a large number of model parameters and sequence lengths at ...

Additionally, single-core, dual-core, and quad-core with scalable task mappings such as multiple models, data parallelism, and tensor parallelism are available. ENLIGHT Pro incorporates a RISC-V CPU ...

The future of IT hardware is rapidly evolving, and by 2025, artificial intelligence (AI) will be the driving force behind ...

A future full of AI agents, postquantum cryptography, hybrid computing and more is speeding your way. What has you most ...

The appetite for AI remains high, and Nvidia's GPUs have become the chip of choice among AI players of all sizes. "We ...