Discover and read the best of Twitter Threads about #compiler
Most recents (2)
GM! Here are the top trending repos in web3, curated by top devs in the last 24 hours ✨.
Check the 6 projects in the thread below 🧵👇🏻
Check the 6 projects in the thread below 🧵👇🏻
Repo openai-cookbook by openai (4565 ⭐️)
+11 new ⭐️ in the last 24h from top devs
Examples and guides for using the OpenAI API
github.com/openai/openai-…
+11 new ⭐️ in the last 24h from top devs
Examples and guides for using the OpenAI API
github.com/openai/openai-…
Repo starknet_in_rust by lambdaclass (32 ⭐️)
+6 new ⭐️ in the last 24h from top devs
A Rust implementation of Starknet
github.com/lambdaclass/st…
+6 new ⭐️ in the last 24h from top devs
A Rust implementation of Starknet
github.com/lambdaclass/st…
#Highlights2021 for me: our #survey on efficient processing of #sparse and compressed tensors of #ML/#DNN models on #hardware accelerators published in @ProceedingsIEEE.
Paper: dx.doi.org/10.1109/JPROC.…
arXiv: arxiv.org/abs/2007.00864
RT/sharing appreciated. 🧵
Paper: dx.doi.org/10.1109/JPROC.…
arXiv: arxiv.org/abs/2007.00864
RT/sharing appreciated. 🧵
Context: Tensors of ML/DNN are compressed by leveraging #sparsity, #quantization, shape reduction. We summarize several such sources of sparsity & compression (§3). Sparsity is induced in structure while pruning & it is unstructured inherently for various applications or sources. 
Likewise, leveraging value similarity or approximate operations could yield irregularity in processing. Also, techniques for size-reduction make tensors asymmetric-shaped. Hence, special mechanisms can be required for efficient processing of sparse and irregular computations.
