Hi, everyone: I am a beginner with Ray, and I’ve always aimed to make the most of my limited personal computing resources. This is probably one of the main reasons why I wanted to learn Ray and its libraries. Hmmmm, I believe many students and individual researchers share the same motivation. Aft…

Hi libeskyi, Welcome to the Ray community! It’s great to hear you’re trying things out :smiley: Is Ray still effective and efficient on a single machine? I would say so, yea! It is designed to parallelize workloads and can utilize multiple cores on a single machine to run concurrent tasks. Howeve…

Hi Christina, Thanks for your warm reply! In fact, resources_per_trial={"gpu": 0.25, "cpu": 10} is my fault. I pasted the code carelessly, sorry for that. In my running code, I set it as resources_per_trial={"gpu": 0.25} which I expected Ray Tune can help me allocate the cpu automatically. As you…

Hmm, okay, a few more things to try out to try and debug this: Ensure you’re not accidentally overriding your ray.init() settings by calling it multiple times. Only one instance should initialize the resources. Try running Ray Debugger to see what’s going on ( Using the Ray Debugger — Ray 2.42.0 ) M…

Hi, @christina , thanks for your kind assistance~ This is my latest ray parallel experiments script: import os import ray from ray import tune from ray.tune import CLIReporter from ray.tune.schedulers import ASHAScheduler from Simulation import run_simulations # Trainable object in Ray Tune from u…

The output of ray status is: [ray status]

The output of watch -n 1 nvidia-smi is: [watch -n 1 nvidia-smi]

Hello!! Sorry for the late reply. I was out of office for a few days but I am back and catching up on threads. I think this might be because you are on local_mode = True. I took a look at some older threads like this one: What is local mode? It will run things in series instead of in parallel. …

Parallelly running experiments with Ray Tune on a single Machine

Ray Tune

libeskyi February 15, 2025, 10:32am 6

The output of ray status is:

ray status1484×860 46.5 KB

Topic		Replies	Views
Ray Tune not running enouch processes Ray Tune	1	354	November 29, 2022
Training trials in parallel on multi-gpu machine Ray Tune	8	1859	August 23, 2021
Resources not being used Ray Core	4	1356	September 21, 2021
Ray doesn't use all CPUs Ray Tune	0	330	March 10, 2024
Best Practices for Optimizing Ray Tune Trials RLlib	2	72	June 19, 2025

Parallelly running experiments with Ray Tune on a single Machine

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