Rapids
RAPIDS is an open-source suite of software libraries developed by NVIDIA, designed to accelerate data science workflows through GPU computing. By leveraging the power of NVIDIA GPUs, RAPIDS enables high-performance data processing and analytics, significantly speeding up operations compared to traditional CPU-based libraries like Pandas. The core library, cuDF, mimics the Pandas API, making it easier for data scientists to transition to GPU-accelerated workflows without a steep learning curve. RAPIDS is particularly beneficial for large datasets and complex computations, making it a valuable tool in the fields of data science and machine learning.
Pandas vs Polars vs Rapids: What’s the Most Convenient for a Laptop?
Stepping into the ever-evolving realm of data analysis, the choice of the right library for data processing has become important. In this dynamic landscape, Pandas, Polars, and Rapids emerge as formid...
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Feature Engineering with RAPIDS: NFL Data Bowl
Before starting this article, I want to ease your skepticism of switching from pandas to RAPIDS cudf, RAPIDS cudf uses the same API as pandas! RAPIDS is moving traditional Data Science workflows on…
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Quick Install Guide: Nvidia RAPIDS + BlazingSQL on AWS SageMaker
RAPIDS was announced on October 10, 2018 and since then the folks in NVIDIA have worked day and night to add an impressive number of features each release. The preferred installation methods…
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Ferris the crab, unofficial mascot for Rust Rust is a programming language released in 2015 that promises performance and reliability. I’ve been looking to build some side projects that I can let run ...
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Threads in Rust allow running parts of a program concurrently. Using threads can significantly reduce the time required to run tasks that can be executed in parallel. Rust’s standard library provides ...
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Making Redux in Rust
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