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• Performance Evaluation of RTX 3080 10G in ffmpeg Transcoding

  26 juin 2023, par JoeLin

  My GPU is RTX 3080 10G ,in ffmpeg , command is :

  


  ffmpeg -loglevel level+info
  
-n -hide_banner -hwaccel cuda -hwaccel_device 0 -hwaccel_output_format cuda
  
-i test.mkv
  
-map 0
  
-c:a copy -preset slow -g 50 -bf 2 -rc:v vbr -cq:v 20 -c:v : h264_nvenc -b:v : 3500k -maxrate:v:0 3500k -bufsize:v:0 7000k -map a:0 -var_stream_map "v:0,a:0,name:1080"
  
"/data/joe/speed/1080_test.mp4"
  
-benchmark

  


  My video file is 3.5G and it takes 27 minutes to execute this command. Can you please tell me if this is within a reasonable range ? By checking the logs, I found that the speed is 7.0x. I would like to know how efficient the transcoding capability of RTX 3080 is and if there are any GPUs with a similar price range that offer better transcoding performance. Alternatively, could there be an issue with my command parameters ? Thank you for your help, guys !

  


  I haven't found similar documentation, so I'm unsure if it's due to an issue with my command

  


• checkasm/arm : preserve the stack alignment checkasm_checked_call

  12 juillet 2016, par Janne Grunau

  checkasm/arm : preserve the stack alignment checkasm_checked_call
  The stack used by checkasm_checked_call_vfp was a multiple of 4 when the
  
  checked function is called. AAPCS requires a double word (8 byte)
  
  aligned stack public interfaces. Since both calls are public interfaces
  
  the stack is misaligned when the checked is called.
  Might fix the SIGBUS error in the armv7-linux-clang-3.7 fate config.
  

  • [DBH] tests/checkasm/arm/checkasm.S

• Extracting audio from video using fluent-ffmpeg

  12 mars, par Idi Favour

  Im trying to extract the audio from a video, an error is occuring
Error converting file : Error : ffmpeg exited with code 234 : Error opening output file ./src/videos/output-audio.mp3.
Error opening output files : Invalid argument

  


  I use this same directory for my video compression that runs before this one and it works.

  


  ffmpeg()
  .input(url)
  .audioChannels(0)
  .format("mp3")
  .output("./src/videos/output-audio.mp3")
  .on("error", (err) => console.error(`Error converting file: ${err}`))
  .on("end", async () => {
    console.log("audio transcripts");
   
    const stream = fs.createReadStream("./src/videos/output-audio.mp3");
    const transcription = await openai.audio.transcriptions.create({
      file: stream,
      model: "whisper-1",
      response_format: "verbose_json",
      timestamp_granularities: ["word"],
    });
    transcripts = transcription.text;
    console.log(transcription.text);
  })
  .run();