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Best of Both Worlds

  • htugrulbuyukisik
  • 14 Nis 2017
  • 1 dakikada okunur

C language is fast. C# language is flexible. Combine them on CPUs, iGPUs, GPUs and FPGAs. OpenCL is based on a constrained C99 compiler and Cekirdekler API wraps it to make it multi-device performance-aware.

Even a low-end laptop CPU(Celeron N3060) gains 44x speed by moving codes to its embedded iGPU as in this video:

Discrete graphics processors are always faster and generally bottlenecking part is the pci-e bridge.

 
 
 

Comments

Why GPGPU? 

  • Offload image-resize to all GPUs and FPGAs so server feels more relaxed to host websites

  • Move compute-heavy sql table joins to C# side to let sql server handle the data-heavy parts.

  • Make particle physics programs performance-aware, even a mild overclock to one of GPUs will increase overall performance.

  • Write your own genuine kernel code to accomplish multi-GPU computing, easily without getting low-level on host side.

 UPCOMING VERSIONS: 

 

  • Device to device pipelining

 

  • Built-in image resizer functions.

 

  • Built-in matrix-multiplication functions.

 

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