Our great sponsors
-
mpi4jax
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:
I've seen a couple of posts of folks using JAX for scientific computing (e.g. physics) workloads without much issue. The parallel primitives work just as well across multiple CPUs as they do on accelerators. If you're on a cluster, also worth looking into https://github.com/PhilipVinc/mpi4jax.
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a more popular project.
Related posts
- What is the best way to save a csv.file in number only ? PC hangs when my file is more than 2GB
- Large Scale Hydrology: Geocomputational tools that you use
- What does it mean to scale your python powered pipeline?
- Is Numpy always more efficient than Pandas? And how much should we rely on Python anyway?
- Ask HN: Is PySPark a Dead-End?