Parallella Epiphany III- Opinions wanted?
Ash Small, Fri Oct 24 2014, 02:58PMI recieved an E-mail from RS today advertising a new 'super computer' the size of a credit card.
,cl_4293628158,cl_4294959524,cl_4294959177,cl_4293
625764,cl_4293628159Three different versions, any opinions, anyone?
EDIT:
]parallella_manual.pdf[/file]
Re: Parallella Epiphany III- Opinions wanted?
Daedronus, Fri Oct 24 2014, 05:00PM
Looks like a fpga based emulator for their actual silicon.
About 2x the price of the actual fpga.
Daedronus, Fri Oct 24 2014, 05:00PM
Looks like a fpga based emulator for their actual silicon.
About 2x the price of the actual fpga.
Re: Parallella Epiphany III- Opinions wanted?
hen918, Fri Oct 24 2014, 07:19PM
I was following this on kick-starter a while ago. It is a custom ASIC with 16 or 64 individual processing cores, for parallel processing, like hash cracking and machine vision. I wouldn't mind one.
The 16 core processor is the co-processor, the host-processor has an arm CPU combined with an FPGA, for lots of power!
hen918, Fri Oct 24 2014, 07:19PM
I was following this on kick-starter a while ago. It is a custom ASIC with 16 or 64 individual processing cores, for parallel processing, like hash cracking and machine vision. I wouldn't mind one.
The 16 core processor is the co-processor, the host-processor has an arm CPU combined with an FPGA, for lots of power!
Re: Parallella Epiphany III- Opinions wanted?
Steve Conner, Tue Oct 28 2014, 10:18AM
Yes, it is a very powerful (for its size, cost and power budget) parallel computer. The host processor is a Xilinx Zynq, which is a dual core ARM (running Linux) combined with a FPGA on the same chip. I think the FPGA is mainly used to handle communications between the host processor, the Epiphany chip and the external memory, but you can add your own IP for things like display controllers. The FPGA is supported by Xilinx's free toolset, so you don't need to buy anything to start messing with it.
Then you have the Epiphany ASIC. Each of the parallel processing cores is a quite capable device with 32K of local memory and hardware floating point. You can program it in C/C++ using GCC. It supports OpenMP and OpenCL, industry standard parallel processing APIs, or you can make your own. Communication between cores is by the shared memory model.
Steve Conner, Tue Oct 28 2014, 10:18AM
Yes, it is a very powerful (for its size, cost and power budget) parallel computer. The host processor is a Xilinx Zynq, which is a dual core ARM (running Linux) combined with a FPGA on the same chip. I think the FPGA is mainly used to handle communications between the host processor, the Epiphany chip and the external memory, but you can add your own IP for things like display controllers. The FPGA is supported by Xilinx's free toolset, so you don't need to buy anything to start messing with it.
Then you have the Epiphany ASIC. Each of the parallel processing cores is a quite capable device with 32K of local memory and hardware floating point. You can program it in C/C++ using GCC. It supports OpenMP and OpenCL, industry standard parallel processing APIs, or you can make your own. Communication between cores is by the shared memory model.
Re: Parallella Epiphany III- Opinions wanted?
Carbon_Rod, Wed Oct 29 2014, 07:52AM
This architecture physically separates core silicon from memory, and therefore must eventually be limited by its cache. A shared memory model would make this contention and pipeline-miss problem exponentially more problematic.
OpenCL is a buggy abstraction layer with a nonzero transactional cost. Anything that runs with overlapping subproblems essentially thrashes the coordinator algorithms.
The $25 Raspberry Pi has a 16 core GPU (now open source) with DMA access on the SoC.
Even with spacial locality, the gains for some types of problems have a nonlinear relationship to actual performance improvements. However, the FFT works great if you don't need some sort of real-time DSP:
For the $120 price (and the memory copy model),
anyone can buy an older PCIx16 based 200+ core 1GHz+ nVidia card with CUDA .
Note the same restrictions will hold....
and your problem might still be solved first by a i7 CPU from years ago.
There are several FPGA with ASIC CPU hybrid chips that have been around for awhile, but in general are only appropriate for a few set of problems like live video/audio/rf-signal stream processing.
The GCC will usually only guarantee functionality, but it is not even close to a high performance compiler with the machine code it outputs.
Cheers,
Carbon_Rod, Wed Oct 29 2014, 07:52AM
This architecture physically separates core silicon from memory, and therefore must eventually be limited by its cache. A shared memory model would make this contention and pipeline-miss problem exponentially more problematic.
OpenCL is a buggy abstraction layer with a nonzero transactional cost. Anything that runs with overlapping subproblems essentially thrashes the coordinator algorithms.
The $25 Raspberry Pi has a 16 core GPU (now open source) with DMA access on the SoC.
Even with spacial locality, the gains for some types of problems have a nonlinear relationship to actual performance improvements. However, the FFT works great if you don't need some sort of real-time DSP:
For the $120 price (and the memory copy model),
anyone can buy an older PCIx16 based 200+ core 1GHz+ nVidia card with CUDA .
Note the same restrictions will hold....
and your problem might still be solved first by a i7 CPU from years ago.
There are several FPGA with ASIC CPU hybrid chips that have been around for awhile, but in general are only appropriate for a few set of problems like live video/audio/rf-signal stream processing.
The GCC will usually only guarantee functionality, but it is not even close to a high performance compiler with the machine code it outputs.
Cheers,
Re: Parallella Epiphany III- Opinions wanted?
Steve Conner, Sun Nov 02 2014, 11:55AM
While this is true, it is really a critique of the concept of parallel computing itself, not the Epiphany architecture as such. Not all problems in computing can be parallelised efficiently, and none of them can be parallelised automatically, you have to figure that part out yourself.
Steve Conner, Sun Nov 02 2014, 11:55AM
While this is true, it is really a critique of the concept of parallel computing itself, not the Epiphany architecture as such. Not all problems in computing can be parallelised efficiently, and none of them can be parallelised automatically, you have to figure that part out yourself.
Re: Parallella Epiphany III- Opinions wanted?
hen918, Sun Nov 02 2014, 12:58PM
The parallella is a lot more efficient than an old GPU
hen918, Sun Nov 02 2014, 12:58PM
Carbon_Rod wrote ...
...
For the $120 price (and the memory copy model),
anyone can buy an older PCIx16 based 200+ core 1GHz+ nVidia card with CUDA .
Note the same restrictions will hold....
and your problem might still be solved first by a i7 CPU from years ago.
...
...
For the $120 price (and the memory copy model),
anyone can buy an older PCIx16 based 200+ core 1GHz+ nVidia card with CUDA .
Note the same restrictions will hold....
and your problem might still be solved first by a i7 CPU from years ago.
...
The parallella is a lot more efficient than an old GPU
Re: Parallella Epiphany III- Opinions wanted?
Steve Conner, Sun Nov 02 2014, 04:56PM
Depends how you define efficient. Gigaflops per watt? Gigaflops per dollar? Hackaday skulls per week of learning curve?
Steve Conner, Sun Nov 02 2014, 04:56PM
Depends how you define efficient. Gigaflops per watt? Gigaflops per dollar? Hackaday skulls per week of learning curve?
Re: Parallella Epiphany III- Opinions wanted?
hen918, Sun Nov 02 2014, 05:58PM
GFLOPS/W (or GFLOP/J) is how you usually define the efficiency of parallel processors. I was just thinking it would be difficult to put a Nvidia GPU in a battery powered machine vision robot/device, for example.
hen918, Sun Nov 02 2014, 05:58PM
GFLOPS/W (or GFLOP/J) is how you usually define the efficiency of parallel processors. I was just thinking it would be difficult to put a Nvidia GPU in a battery powered machine vision robot/device, for example.
Re: Parallella Epiphany III- Opinions wanted?
Carbon_Rod, Mon Nov 03 2014, 08:13AM
I have seen teams that had several nVidia GPU based laptops running on robot platforms.
More importantly, they actually are able to push the design cycle forward without orphan standards, or board support package problems.
The new Tegra cores are a nice little SoC, but the ASIC codecs are usually where most of the energy efficiency gains are made.
New mobile ARM core SoC processors are more common than desktops now...
Carbon_Rod, Mon Nov 03 2014, 08:13AM
I have seen teams that had several nVidia GPU based laptops running on robot platforms.
More importantly, they actually are able to push the design cycle forward without orphan standards, or board support package problems.
The new Tegra cores are a nice little SoC, but the ASIC codecs are usually where most of the energy efficiency gains are made.
New mobile ARM core SoC processors are more common than desktops now...
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