> The EIB is made of twelve nodes called Ramps, each one connecting one component of Cell... Having said that, instead of recurring to single bus topologies (like the Emotion Engine and its precursor did), ramps are inter-connected following the token ring topology, where data packets must cross through all neighbours until it reaches the destination (there’s no direct path).
I knew IBM was involved in the design of the Cell BE, but I had no idea some successor of IBM's token ring tech (at least the concept of it) lived on in it. I'm sure there's other hardware (probably mainframe hardware) in and before that 2006 with similar interconnects.
So, I'd have to dig through some older notes I have, however, some of this information seems inaccurate based upon my own interpretation of the specs (and writing code...specifically, but not limited to, the PowerPC part). A suggestion from me is to provide sources, and also maybe an epub of this.
The PS3 was used a few time in clusters – some NN work was done on it back in the day. My understanding (somewhat echoed in TFA) is that when programming Cell, you really needed to think about communication patterns to avoid quickly running into memory bandwidth limitations, especially given memory hierarchy and bus quirks.
For it's day, it packed a lot of compute into cheap package, so long as you could do something useful with a data set that fit into 256kB, the size of the local memory buffer on each SPE. If you overflowed that, the anemic system bandwidth would make it suck. Protein folding was an example of a problem that back then used tons of compute but could be fit into small space.
It's a nearly 20 year old gaming console. Even if you could port a deep learning workload to run efficiently on the Cell architecture, it would be thoroughly outclassed by a modern cell phone (to say nothing of a desktop computer).
The PS3 only had 256mb of main memory so you'd be pretty limited there. Memory bandwidth, great at the time, is pretty poor by today's standards (25 gb/s)
> The EIB is made of twelve nodes called Ramps, each one connecting one component of Cell... Having said that, instead of recurring to single bus topologies (like the Emotion Engine and its precursor did), ramps are inter-connected following the token ring topology, where data packets must cross through all neighbours until it reaches the destination (there’s no direct path).
I knew IBM was involved in the design of the Cell BE, but I had no idea some successor of IBM's token ring tech (at least the concept of it) lived on in it. I'm sure there's other hardware (probably mainframe hardware) in and before that 2006 with similar interconnects.
The EIB has nothing to do with 1980s Token Ring and this is arguably a mistake in the article. It's just a ring topology.
So, I'd have to dig through some older notes I have, however, some of this information seems inaccurate based upon my own interpretation of the specs (and writing code...specifically, but not limited to, the PowerPC part). A suggestion from me is to provide sources, and also maybe an epub of this.
Please see this: https://github.com/flipacholas/Architecture-of-consoles
> A suggestion from me is to provide sources, and also maybe an epub of this
What do you mean?
It seems they missed this. https://payhip.com/copetti
[dead]
Can it run deep learning workloads?
The PS3 was used a few time in clusters – some NN work was done on it back in the day. My understanding (somewhat echoed in TFA) is that when programming Cell, you really needed to think about communication patterns to avoid quickly running into memory bandwidth limitations, especially given memory hierarchy and bus quirks.
https://open.clemson.edu/all_theses/629/
For a while, it was a major player in protein folding. I remember the PS3 was particularly apt at doing that sort of work.
For it's day, it packed a lot of compute into cheap package, so long as you could do something useful with a data set that fit into 256kB, the size of the local memory buffer on each SPE. If you overflowed that, the anemic system bandwidth would make it suck. Protein folding was an example of a problem that back then used tons of compute but could be fit into small space.
It's a nearly 20 year old gaming console. Even if you could port a deep learning workload to run efficiently on the Cell architecture, it would be thoroughly outclassed by a modern cell phone (to say nothing of a desktop computer).
https://en.wikipedia.org/wiki/PlayStation_3_cluster
Eugh, maybe?
The PS3 only had 256mb of main memory so you'd be pretty limited there. Memory bandwidth, great at the time, is pretty poor by today's standards (25 gb/s)