This is software documentation for the Collective Knowledge framework v1.15.0. Related resources: "Enabling reproducible ML and systems research: the good, the bad, and the ugly" (invited talk at FastPath'20 at ISPASS'20) "MILEPOST Project Experience: building ML-based self-optimizing compiler" (invited talk at Google compile+ML seminar) "The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps" (arXiv:2006.07161
We will discuss and analyze the concept and the role of knowledge produced in online social communit...
Nowadays, engineers have to develop software often without even knowing which hardware it will event...
Empirical auto-tuning and machine learning techniques have been showing high potential to improve ex...
Developing novel applications based on deep tech (ML, AI, HPC, quantum, IoT) and deploying them in p...
This presentation introduces Collective Knowledge Playground - a free, open-source and technology-ag...
Invited talk at Google compiler+ML seminar I was asked to share my experience with the MILEPOST pro...
Validating experimental results from articles has finally become a norm at many HPC and systems conf...
Validating experimental results from articles has finally become a norm at many HPC and systems conf...
Invited talk at FastPath 2020 (International Workshop on Performance Analysis of Machine Learning Sy...
The keynote presentation from the 1st ACM conference on reproducibility and replicability (ACM REP'2...
Invited talk at FastPath 2020 (International Workshop on Performance Analysis of Machine Learning Sy...
International audienceDesigning, analyzing and optimizing applications for rapidly evolving computer...
I started drafting this document at the beginning of the development of the 3rd version of plugin-ba...
International audienceEmpirical auto-tuning and machine learning techniques have been showing high p...
The original presentation was shared via SlideShare. Validating experimental results from articles ...
We will discuss and analyze the concept and the role of knowledge produced in online social communit...
Nowadays, engineers have to develop software often without even knowing which hardware it will event...
Empirical auto-tuning and machine learning techniques have been showing high potential to improve ex...
Developing novel applications based on deep tech (ML, AI, HPC, quantum, IoT) and deploying them in p...
This presentation introduces Collective Knowledge Playground - a free, open-source and technology-ag...
Invited talk at Google compiler+ML seminar I was asked to share my experience with the MILEPOST pro...
Validating experimental results from articles has finally become a norm at many HPC and systems conf...
Validating experimental results from articles has finally become a norm at many HPC and systems conf...
Invited talk at FastPath 2020 (International Workshop on Performance Analysis of Machine Learning Sy...
The keynote presentation from the 1st ACM conference on reproducibility and replicability (ACM REP'2...
Invited talk at FastPath 2020 (International Workshop on Performance Analysis of Machine Learning Sy...
International audienceDesigning, analyzing and optimizing applications for rapidly evolving computer...
I started drafting this document at the beginning of the development of the 3rd version of plugin-ba...
International audienceEmpirical auto-tuning and machine learning techniques have been showing high p...
The original presentation was shared via SlideShare. Validating experimental results from articles ...
We will discuss and analyze the concept and the role of knowledge produced in online social communit...
Nowadays, engineers have to develop software often without even knowing which hardware it will event...
Empirical auto-tuning and machine learning techniques have been showing high potential to improve ex...