Video Transcoding Software Full Specifications Whats
Video Transcoding Software Mac Mac Most

Video Transcoding Software Mac Mac Most

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IPVTL provides high density transcoding capability with lowest latency.

It has full support of media encodings commonly being used today, such as G.711(PCM), MP23, AMR, AAC, AC3, H.263(), H.264SVC, H.265HEVC, MPEG-1, MPEG-2 and MPEG-4, also including HTML5 video codec VP8.

It works well with popular media streaming servers including Windows Media Server, RealNetworks Helix Server, Adobe Flash Media Server or Wowza Media Server, and also most DVB source devices in the market.

It can stream from any stored movie clips on your disk or any video capture sources including webcam, DCDV and TV tuner cards, with transcoding on the fly.

IPVTL let you to have full control of video and audio encoding profiles as per your system requirements.

Video resolution, quality, frame rate and bit rate, you can reshape your video stream fast and simple.

With live stream time shifting feature included, scheduling delayed streaming between different time zones is possible.

Video Transcoding Software Full Specifications Whats

Full Specifications Whats new in version 5.5.2.8 General Release October 21, 2015 Date Added October 21, 2015 Version 5.5.2.8 Operating Systems Operating Systems Windows 10, Windows 2003, Windows Vista, Windows, Windows 2000, Windows 8, Windows Server 2008, Windows 7, Windows XP Additional Requirements None Popularity Total Downloads 6,295 Downloads Last Week 3 Report Software Related Software Mezzmo Free Organize media files and watch them on your favorite digital devices.

But if the CPU is not strong enough, or you can replace the CPU, GPU acceleration will always offer extra enhancements.

Here well explain how GPU transcodes videos and outperforms CPU processing.

GPU is a computer hardware chip designed for rapid calculations.

Its able to process images faster than a CPU due to its parallel processing architecture.

Developed by NVIDIA in 2007, GPU has evolved into a popular choice for resource-intensive tasks.

To put it simply, its kind of close cooperation between CPU and GPU which makes most of their advantages: CPU starts and ends the task, while GPU manages the heavy video decoding encoding.

Though there are two major GPU accelerated video transcoders- AMD and Nvidia NVENC hardware transcoding (see the last section), they work similarly.

Then the compressed video data will be transmitted to the graphic memory of GPU.

The GPU comprises graphics, video, audio, and display capabilities, and it will carry out all the decoding, encoding and post-processing tasks.

During this resource- and time-intensive process, CPU is freed up to provide sufficient compute capability for gaming or other tasks on computer.

Step 3. After the GPU video transcoder finishes the video processing, GPU sends the results back to CPU.

Then CPU tells the software that the task is completed and the program outputs the transcoded file.

On the contrary, GPU is not good at dealing complicated tasks on a single or few streams of data.

In other words, GPU is a special-purpose CPU which is mostly beneficial in high-resolution environments, especially for accelerating 2K or 4K UHD video processing.

B CPU. CPU has fewer cores than GPU, but each core is more efficient than that of GPU.

Its much faster handling single or few streams of data, but not as good at handling multiple tasks simultaneously.

In comparison, a CPU is like a worker who is fast for different jobs.

A GPU is like a group of clone workers who are super fast in union, but created for the same tasks only.

What about GPU vs CPU video transcoding performance Numbers paint a thousand words, lets check the test data.

Overall, GPU has a 2 to 3x faster speed under the same configurations.

That being said, the higher the resolution, the greater the benefits will be realized from GPU-acceleration transcoding.

While CPU usage shoots up to 80 to 100 when transcoding without GPU acceleration.

The higher CPU load easily freezes the computer and leads to choppy results.

Therefore, the performance difference between different GPUs is very small.

Meanwhile, the impact of different CPU on GPU transcoding is not big either.