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Hello every body,
What is the solution for : "Kernel Restarting The kernel appears to have died. It will restart automatically" Error ?
its definitely not a problem of loaded data ! I use barely two months of daily resolution data !
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Link Liang
Hi Hicham,
We cannot reproduce the error mentioned. The error message does not narrow down the potential causes, as there could be many things that went wrong and lead to it. Would you mind to share your notebook or code so that we could address your problem in details?
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Hicham OURIAGHLI
Hi sir,
I found the problem, it's basically the calculation unit which is not sufficient, wasn't enough to run the algorithm, finally I reduced the number of iterations and it works.
By the way I have a quick question. In real backtest of this algorithm, I will need a larger calculation unit, I'm wondering if the GPU's for backtesting are larger ?
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Link Liang
Hi Hicham,
Our backtesting environment has less limitations compared to research environment. When we make a big history request, it takes some time to fetch the data and create pandas data frames and the kernel may timeout for inactivity during the process. because of that, we need to make smaller requests.
Another option is to download Lean and run the algorithm on your local environment. Hope it helps!
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Hicham OURIAGHLI
Thanks Sir, I'll try it
Thank you soo much
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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