InfoQ

Hybrid Cloud Data at Uber: How Engineers Solved Extreme-Scale Replication Challenges

Uber’s HiveSync team optimized Hadoop Distcp to handle multi-petabyte replication across hybrid cloud and on-premise data lakes. Enhancements include task parallelization, Uber jobs for small ...
Semiconductor Engineering

Step Towards A 5G Software-Defined RAN Over A Fully Open-Source Parallel RISC-V Architecture (ETH Zurich)

A technical paper titled “Efficient Parallelization of 5G-PUSCH on a Scalable RISC-V Many-core Processor” was published by researchers at ETH Zurich. “5G Radio access network disaggregation and ...
SiliconANGLE

RapidFire AI applies parallelization to speeding RAG workflows

Startup RapidFire AI Inc. today released an open-source software package aimed at simplifying the development of the pipelines that are increasingly central to enterprise artificial intelligence ...
marktechpost

Hugging Face Releases Picotron: A Tiny Framework that Solves LLM Training 4D Parallelization

The rise of large language models (LLMs) has transformed natural language processing, but training these models comes with significant challenges. Training state-of-the-art models like GPT and Llama ...
Geeky Gadgets

Multiple 3D Printing Heads Slash Print Times by 85%

Imagine a world where the wait for your 3D-printed masterpiece shrinks from a day and a half to just a few hours. It sounds like a dream, right? If you’ve ever felt the frustration of watching your ...
IEEE

Parallelization Strategies for DLRM Embedding Bag Operator on AMD CPUs

Abstract: Deep Learning Recommendation Models (DLRM) are deployed extensively to support personalized recommendations and consume a large fraction of AI cycles in modern datacenters with embedding ...
CoinTelegraph

Monad’s $225M funding: Optimistic parallelization and MonadBFT insights

Monad Labs raised $225 million, led by Paradigm, pushing forward the discussion on parallelized EVM chains. Monad is a new layer-1 smart contract platform that recently raised $225 million in funding ...
marktechpost

Apple Researchers Propose KV-Runahead: An Efficient Parallel LLM Inference Technique to Minimize the Time-to-First-Token

Large language models (LLMs), particularly Generative Pre-trained Transformer (GPT) models, have demonstrated strong performance across various language tasks. However, challenges persist in their ...
IEEE

Parallelization of the Shift and Add Reducer

Abstract: This paper discusses a novel method for parallelization of a Shift and Add Reducer. This improvement allows for high levels of parallelization and decreases the number of cycles required for ...