Honored Contributor
Honored ContributorWith hardware you already have, you have a couple different ways you can go.
1) NIOS + C software in board + your custom IP component doing your math. See: https://www.altera.com/support/support-resources/design-examples/intellectual-property/embedded/nios-ii/exm-hardware-tutorial.html Your NIOS C software can include the "Host Based Filesystem" so your C code can use <stdio.h> to open your file, read some binary data, write it to your custom IP component math block, read the result back, write the result to binary file. If you are OK with C on an embedded processor, this path works fine and the FPGA on your board has enough resources to go down this road at least for beginnings. 2) TCL script + Altera System Console + your custom IP component doing your math. See this user contributed tutorial: http://www.alterawiki.com/wiki/using_the_usb-blaster_as_an_sopc/qsys_avalon-mm_master_tutorial If you aren't OK with C on an embedded processor, you can use TCL on the PC to read your binary file, write the inputs, read the results, write the results to binary file. You have almost all the FPGA resources available for your processing and you don't have to familiarize yourself with NIOS IDE for software development. I do not believe OpenCL is supported targetting the board you already have. See this document for supported development boards: https://www.altera.com/content/dam/altera-www/global/en_us/pdfs/products/software/opencl/opencl-dev-kit-guide.pdf Creating your own IP component, there are several tutorials. Here is one video: https://www.youtube.com/watch?v=v6rhbvablo8 Another thing you can do, if you go the NIOS route, is work with Custom Instructions instead of Avalon-MM Slave based peripheral components. Either way is fine for getting started, but Custom Instructions aren't really applicable going forward to a ARM SoC future. Custom Instructions are a good fit sometimes if you have a body of C/C++ code which compiles and runs fine on the NIOS - depending on what you're doing you can then get huge gains in performance by pushing kernels of your image processing down to hardware. Coming from Matlab though and not having a background in FPGA development, you will probably get better trade off [more automation/tool support] investing in the OpenCL route. Finally: Altera has some good online [free] training videos that if nothing else will walk you through the basics of many things. https://www.altera.com/support/training/overview.html https://www.altera.com/support/training/course.html?coursecode=odswbecome https://www.altera.com/support/training/course.html?coursecode=oqsys3000
