TornadoVM
jr
TornadoVM | jr | |
---|---|---|
22 | 4 | |
1,123 | 114 | |
2.8% | - | |
9.9 | 9.4 | |
6 days ago | 2 months ago | |
Java | Go | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
TornadoVM
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Intel Gaudi 3 AI Accelerator
You don't need to use C++ to interface with CUDA or even write it.
A while ago NVIDIA and the GraalVM team demoed grCUDA which makes it easy to share memory with CUDA kernels and invoke them from any managed language that runs on GraalVM (which includes JIT compiled Python). Because it's integrated with the compiler the invocation overhead is low:
https://developer.nvidia.com/blog/grcuda-a-polyglot-language...
And TornadoVM lets you write kernels in JVM langs that are compiled through to CUDA:
https://www.tornadovm.org
There are similar technologies for other languages/runtimes too. So I don't think that will cause NVIDIA to lose ground.
- Java VectorAPI compatiblity with TornadoVM GPU programming framework
- Java GPU pre/post processing with ONNX RT and TornadoVM
- FLaNK Stack 05 Feb 2024
- FLaNK 25 December 2023
- GPU Acceleration for Python, JavaScript, Ruby from Java with Truffle
- TornadoVM v1.0 Released
- TornadoVM 1.0
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From CPU to GPU and FPGAs: Supercharging Java Applications with TornadoVM [video]
Presented by Juan Fumero, PhD & Research Fellow (The University of Manchester, UK) during the JVM Language Summit 2023 (Santa Clara CA).
More information on TornadoVM can be found at https://www.tornadovm.org/
Tags: #Java #JVMLS #GPU #FPGA #OpenJDK #GraalVM #AI
jr
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JR, quality Random Data from the Command line, part II
We have seen how to use JR in more advanced use cases, streaming quality random data with referential integrity. In the next part of this series, we will see how to use REST apis with JR. In the meanwhile, happy streaming!
- FLaNK Stack Weekly for 22 May 2023
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JR, quality Random Data from the Command line, part I
Datagen is the de-facto standard to generate random data for Kafka. But customising what's generated is not something you can do in 30 seconds, and enabling compression is currently not an option with the managed connectors. So I decided to write a tool which you could use to easily start streaming random data to kafka in seconds, and that's why JR was born. With the help of some friends and colleagues we packed JR with a lot of features (and many more coming!)
What are some alternatives?
Aparapi - The New Official Aparapi: a framework for executing native Java and Scala code on the GPU.
kcat - Generic command line non-JVM Apache Kafka producer and consumer
openapi4j - OpenAPI 3 parser, JSON schema and request validator.
docker-compose-viz - Docker compose graph visualization
GraalVMREPL - REPL (read–eval–print loop) shell built on top of JavaFX and GraalVM stack, incorporating GraalJS, GraalPython, TruffleRuby and FastR
junodb - JunoDB is PayPal's home-grown secure, consistent and highly available key-value store providing low, single digit millisecond, latency at any scale.
kattlo-cli - Kattlo CLI Project
flink-statefun - Apache Flink Stateful Functions
schema-registry-statistics - Schema Registry Statistics Tool
StableStudio - Community interface for generative AI
Redis - Redis is an in-memory database that persists on disk. The data model is key-value, but many different kind of values are supported: Strings, Lists, Sets, Sorted Sets, Hashes, Streams, HyperLogLogs, Bitmaps.