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How reliable are the power delivery in laptops

How reliable are the power delivery in laptops

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Ender_Craft47
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09-15-2018, 09:02 PM
#11
Capacitors are sensitive to heat, which is why I try to keep them cool over time. The CPU and other parts don’t mind operating at maximum levels.
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Ender_Craft47
09-15-2018, 09:02 PM #11

Capacitors are sensitive to heat, which is why I try to keep them cool over time. The CPU and other parts don’t mind operating at maximum levels.

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kirito__101
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09-16-2018, 05:32 AM
#12
Almost all caps are capable of withstanding temperatures above 100°C for Jurrunio.
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kirito__101
09-16-2018, 05:32 AM #12

Almost all caps are capable of withstanding temperatures above 100°C for Jurrunio.

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wither240
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09-16-2018, 07:21 AM
#13
Also think about the performance—CPUs for machine learning are much slower than GPUs. It’s better to save your battery life instead of barely improving speed by a small margin.
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wither240
09-16-2018, 07:21 AM #13

Also think about the performance—CPUs for machine learning are much slower than GPUs. It’s better to save your battery life instead of barely improving speed by a small margin.

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Star_Lars
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09-16-2018, 11:20 AM
#14
Most solid capacitors last around 200,000 hours, while coils typically last about 100,000 hours—this can vary based on gauge and winding count. Chemical capacitors usually have shorter lifespans and are sensitive to heat, so be careful when purchasing used or vintage equipment.
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Star_Lars
09-16-2018, 11:20 AM #14

Most solid capacitors last around 200,000 hours, while coils typically last about 100,000 hours—this can vary based on gauge and winding count. Chemical capacitors usually have shorter lifespans and are sensitive to heat, so be careful when purchasing used or vintage equipment.

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ITz_NoY
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09-22-2018, 03:43 PM
#15
GPUs are significantly quicker, yet it's important to note that many data conversions must occur before the GPU can effectively train, which appears to be happening with OP since both CPU and GPU are under strain.
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ITz_NoY
09-22-2018, 03:43 PM #15

GPUs are significantly quicker, yet it's important to note that many data conversions must occur before the GPU can effectively train, which appears to be happening with OP since both CPU and GPU are under strain.

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FOSTREX
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09-26-2018, 05:32 AM
#16
This situation is clear, and the CPU handles loading batches and managing GPU scheduling. Even without a data preparation step, it will still use the CPU for certain tasks. We don't know precisely which operations deep learning frameworks are executing in the background.
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FOSTREX
09-26-2018, 05:32 AM #16

This situation is clear, and the CPU handles loading batches and managing GPU scheduling. Even without a data preparation step, it will still use the CPU for certain tasks. We don't know precisely which operations deep learning frameworks are executing in the background.

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