NVIDIA AI has announced a live session showing how to run Polars, a popular open-source DataFrame library, on GPUs in Amazon Web Services (AWS) using cuDF Polars.
NVIDIA · Live session on AWS
Bringing Polars DataFrames onto GPUs in the cloud
NVIDIA is hosting a hands-on session on running Polars, a popular open-source DataFrame library, on GPUs in Amazon Web Services using cuDF Polars, while keeping the familiar Polars interface.
The move in one flow
Same Polars code, different execution path
Start
Polars on CPU
Filter, join and transform large tables on processors.
→
Bridge
cuDF Polars
NVIDIA's GPU-accelerated engine, part of RAPIDS.
→
Result
GPUs on AWS
Supported operations offloaded to GPU hardware in the cloud.
Why it matters
Keeps the familiar Polars programming interface
Targets teams running data pipelines in the cloud
Tests GPU acceleration without building infrastructure from scratch
Extends NVIDIA's GPU software stack into everyday data processing
What to watch
Gains depend on the workload and data types
Only supported operations run on the GPU
Real-world production performance is still to be proven
Compatibility should be checked against each pipeline
Before you expect results
Speedup is conditional. Test your own pipeline first.
Workload
Does your job suit GPU processing?
Data types
Are your columns supported by cuDF Polars?
Operations
Which steps fall back to the CPU?
AWS deployment
How easily can your team run it in production?
Session details
The date, agenda and speakers are not specified in the available material. Confirm them through NVIDIA's official channels.
Continue reading The rest of this article is for AI News Blitz readers. Choose an option below to keep reading.
Already purchased? Sign in ✓ Signed in — this article isn’t included in your current plan.Unlocking the full article...