234 points by parallel_wizard 1 year ago flag hide 18 comments
johntech 1 year ago next
Great article on parallelizing distributed systems! It's a topic that has always interested me.
codingcat 1 year ago next
I completely agree, John! I wonder if the techniques discussed here could be applied to blockchain technology?
codingcat 1 year ago next
Excellent point, blockchainbob!
blockchainbob 1 year ago prev next
This is definitely a relevant topic in the blockchain space. distributed systems and parallelism are integral to blockchain technology.
bigdatabill 1 year ago prev next
I'm glad you all are finding this interesting. I recently parallelized a distributed system in my big data project and it made a huge difference.
johntech 1 year ago next
Wow, bigdatabill! I'd love to hear more about your experience with this. What tools did you use?
bigdatabill 1 year ago next
I used Apache Spark for the parallelization, John. It was a bit of a learning curve but it was definitely worth it in the end.
blockchainbob 1 year ago prev next
That's really interesting, bigdatabill! Have you tried implementing these techniques in a blockchain context?
bigdatabill 1 year ago next
Not yet, blockchainbob, but it's definitely something I would consider in the future. It seems like there could be a lot of potential for performance improvements.
datadan 1 year ago prev next
I'm curious if anyone here has experience with parallelizing distributed systems in a cloud environment like AWS?
johntech 1 year ago next
I haven't tried it personally, datadan, but I've heard of people using tools like Kubernetes to manage parallelization in a cloud environment.
bigdatabill 1 year ago prev next
Datadan, you might also want to look into AWS's own parallel computing capabilities. They have a service called the AWS ParallelCluster that could be useful for your needs.
blockchainbob 1 year ago prev next
I've heard it's also possible to use serverless technologies like AWS Lambda to parallelize distributed systems in the cloud. Just something to consider!
machinelearningmike 1 year ago prev next
Parallelizing distributed systems is definitely a hot topic in the machine learning space. It's crucial for training large models with lots of data.
johntech 1 year ago next
Absolutely, machinelearningmike. I've seen researchers using parallelism to train models on huge datasets like ImageNet in just a few hours.
datadan 1 year ago prev next
I agree, machinelearningmike. I'm currently working on a computer vision project and efficient parallelization has been key to making progress.
bigdatabill 1 year ago prev next
Parallelism is definitely the way to go if you want to scale your machine learning models. I've had a lot of success using tools like TensorFlow's ParallelFor and ParallelIterator classes.
machinelearningmike 1 year ago next
That's a great tip, bigdatabill! I've used TensorFlow a lot but I hadn't heard of those classes before.