Row 4479

Row ID: 4479 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 4479 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I used to have a dell g7 rtx 2060, which I used for daily usage,training and inference. I read there was some metal programming support in MacBooks Ms. I have become a used to the ease and speed(i keep a lot of tabs open) and a Mac build provides over a heavily loaded gaming laptop(where the OS itself takes a lot of the RAM). Does MacBook series provide the expected GPU speedup like nvidia cuda does? Or is it comparible.

FieldValue
text I used to have a dell g7 rtx 2060, which I used for daily usage,training and inference. I read there was some metal programming support in MacBooks Ms. I have become a used to the ease and speed(i keep a lot of tabs open) and a Mac build provides over a heavily loaded gaming laptop(where the OS itself takes a lot of the RAM). Does MacBook series provide the expected GPU speedup like nvidia cuda does? Or is it comparible.
label r/pytorch
dataType post
communityName r/pytorch
datetime 2024-04-13
username_encoded Z0FBQUFBQm5LakwxbkYxTndyR2hFUFg5dHpUSDFHWGNDUHV4VUlaR2xSNEpTeDQ0V1M5U193T0h6YjF5WDdQS3V6eUh0d0ZMNEgxczduZGtlWWtMaEFuMFdmX0FKb0dLZlE9PQ==
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Raw Record

{
  "text": "I used to have a dell g7 rtx 2060, which I used for daily usage,training and inference. \nI read there was some metal programming support in MacBooks Ms. I have become a used to the ease and speed(i keep a lot of tabs open) and a Mac build provides over a heavily loaded gaming laptop(where the OS itself takes a lot of the RAM). Does MacBook series provide the expected GPU speedup like nvidia cuda does? Or is it comparible.",
  "label": "r/pytorch",
  "dataType": "post",
  "communityName": "r/pytorch",
  "datetime": "2024-04-13",
  "username_encoded": "Z0FBQUFBQm5LakwxbkYxTndyR2hFUFg5dHpUSDFHWGNDUHV4VUlaR2xSNEpTeDQ0V1M5U193T0h6YjF5WDdQS3V6eUh0d0ZMNEgxczduZGtlWWtMaEFuMFdmX0FKb0dLZlE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9GNW1NNU4zZ00wOHFRUERLREFZX0dLSGVmUEpuaUx3NEtIX3R4dG1IMFlCNjBidzlUaFN4ZWZfVHdXLURnRU9ta2w3ekZUdEtpc1ZsT0VMcGFheWM2SF9SUVEzbGMxYU93REg2cDFHWlMwRjdJQU02RHhBVlV1S2ZtZ0I4aldiNV85Vm8xZDYxZE1PTVNDWGt6VWNuQWpIcDZIaHVUQi16Y0FIVnlKMXhGaUo4PQ=="
}

Entry Information