deRerum

5 ms·

1.
by deRerum 7y ago
Yes the examples you have all have multiple processing elements but they are vector processors. I was talking about simple and cheap scalar processors. GPUs rely on symmetry to simplify the hardware design. Multiple (like 64) processing ele
2.
by deRerum 7y ago
That is an interesting idea. I wonder if a small processor core could be stamped out on an fpga and hundreds of small processors can run simultaneously. Then I wish my c++ objects each ran in a separate (virtual) processor instance. They co
3.
by deRerum 7y ago
Anyone can prefetch data into the cache, but letting programmers control cache eviction would open the door to all kinds of user errors which would kill performance.
4.
by deRerum 7y ago
A 10Mhz processor has a clock cycle of 100ns (0.1 millionths of a second). Those are just rough representative numbers I picked...any particular RAM delays would be different and the actual latency would be complicated by bus speeds and pro
5.
by deRerum 7y ago
In the past (like around the time most programming languages were invented) memory speeds were faster than processor speeds. So all variable accesses were instantaneous. Languages like C did not have to worry about memory hierarchies. If me
6.
by deRerum 7y ago
GPUs are latency hiding engines...they address the mismatch between processor clock speeds and memory latency by a unique scheme. Since they can’t improve memory latency, instead they parallelize memory and vastly increase the bandwidth ava
7.
by deRerum 10y ago
Agreed. Way back when, when I was young and stupid and knew everything, my head was full of logic puzzles and programming tricks. So it was easy to solve them in an interview. But today, there are so many things in my head that I cannot ke