Category Archives: Opencl

Khronos publishes a range of specs to take GPU computing to the Web, C++

After releasing OpenGL ES 3.1 on Monday, the Khronos Group today announced a handful of other specifications for 3D graphics and GPU computation, including WebCL.

Just as WebGL defines a JavaScript API for OpenGL ES 2.0 3D graphics, WebCL defines a JavaScript API for OpenCL 1.1 parallel computation. If WebCL receives the same kind of industry adoption that WebGL has, it will enable mobile developers to perform tasks such as physics calculations in games and image processing, all accelerated by the GPU, or even multiple cores of the CPU.

As with WebGL, WebCL is a fairly low-level API. It works the same way as OpenCL does on the desktop: OpenCL routines need to be written in OpenCL’s special C-derived language. This will make it familiar to existing OpenCL developers and enable the reuse of existing OpenCL code, but it’s unlikely to be something that traditional Web developers are familiar with.

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A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.


    







A Look at Altera’s OpenCL SDK for FPGAs

FPGAs offer the promise of reconfigurable computing: Reconfiguring the hardware to match your application needs. This reconfigurable approach is often more efficient than general purpose processors such as CPUs. However, programming FPGAs has traditionally been hard and usually required expertise in Hardware Description Languages (HDLs). Altera has introduced an OpenCL SDK for FPGAs, making them accessible to a much larger software community and a potential alternative to other accelerators such as GPGPUs. We take a look at Altera's offering, explain how it works and provide analysis about how using OpenCL for FPGAs compares with alternatives such as GPUs.