As I described here, Power BI can send SQL queries in parallel in DirectQuery mode and you can see from the Timeline column there is some parallelism happening here – the last two SQL queries ...

HB2151 threatens to speed up controversial data center construction statewide Harrisburg, PA — Today, the House Energy Committee held a hearing for HB2151, a Shapiro-backed bill that would provide a ...

SpaceX uses your data to train its machine learning and AI models and might share that with partners who 'help us develop AI-enabled tools that improve your customer experience.' From the laptops on ...

Parallel Learning, a virtual special education platform, secured $20 million in Series B funding to address critical nationwide special education teacher shortages and resource gaps. The company ...

import gc import torch from vllm import LLM, SamplingParams from vllm.distributed.parallel_state import (destroy_distributed_environment, destroy_model_parallel) def clean_up(): destroy_model_parallel ...

For decades, data centers were designed with permanence in mind: fixed plans, rigid shapes and predictable life cycles. Physical constraints of legacy architectures made them inherently static. But in ...

Comprehensive Training Pipelines: Full support for Diffusion Language Models (DLMs) and Autoregressive LMs, from pre-training and SFT to RL, on both dense and MoE architectures. We strongly recommend ...

NVIDIA's NVL72 systems are transforming large-scale MoE model deployment by introducing Wide Expert Parallelism, optimizing performance and reducing costs. NVIDIA is advancing the deployment of ...

In a new paper, researchers from Tencent AI Lab Seattle and the University of Maryland, College Park, present a reinforcement learning technique that enables large language models (LLMs) to utilize ...

What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...

Abstract: With the rapid adoption of large language models (LLMs) in recommendation systems, the computational and communication bottlenecks caused by their massive parameter sizes and large data ...