MarktechPost·
In this article we look at YaFF, Yandex's open-source zero-copy wire format for the Protobuf ecosystem. We keep the .proto file as the single source of truth, changing only how data sits in memory. We walk through its four layouts — Fixed, Flat, Sparse, and Dynamic — and the benchmark where Flat Layout reads within 1.2× of a raw C++ struct. We also cover where it fits, including the advertising recommendation system reporting 10–20% CPU savings at production scale. The post Yandex Open-Sources YaFF: A Zero-Copy Wire Format for Protobuf With Near-Struct Read Speed appeared first on MarkTechPost.
Read full articleBeat the 8GB VRAM limit. Learn how to run three different LLMs on a single 8GB GPU using C++ layer multiplexing and admission control. The post 3 Agents. 3 LLMs. 1 Aging GPU: Engineering Parallel Inference on Bare Metal appeared first on Towards Data Science.
Dynamic's integration with Aleo could revolutionize privacy in crypto transactions, but regulatory challenges may impact its widespread adoption. The post Dynamic becomes first wallet provider to support embedded private payments on Aleo appeared first on Crypto Briefing.
If Python developers have one consistent gripe about their beloved language, it tends to be this: Why is it so hard to take a Python program and deploy it as a standalone artifact, the way C, C++, Rust, Go, and even Java can be deployed? Are we stuck with requiring everyone to install the Python runtime first before they can use a Python program? And why are all the workarounds for this problem so clunky? One of the features that makes Python so appealing — its dynamism — is also the reason Python apps are so difficult to bundle and deploy. Not impossible, but challenging. Bundled Python apps end up being big packages, never less than a dozen megabytes or more. Plus, the tools for creating those bundles aren’t the friendliest or most convenient. So what is it about Python’s dynamism that’s reponsible for this? The pleasures and perils of Python’s dynamism When we talk about Python as a “dynamic” language, that means more than the fact that Python apps are executed with an interpreter.
