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Inderpreet Singh

Relation between TFLOPS and Threads in a GPU?

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What's the relation between Teraflops and Threads in a GPU like GTX Titan X has 7 TFOPS of Compute Performance but how many threads it has ?

If they are different concepts. Can you please explain both of them?

Edited by Inder

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Peak performance (in FLoating point OPerations per Second = FLOPS) is the theoretical upper limit on how many computations a device can sustain per second. If a Titan X were doing nothing else than computing 1 + 2 * 3 then it could do that 3 072 000 000 000 times per second and since there are two operations in there (an addition and a multiplication) this amounts to 6 144 000 000 000 FLOPS or about 6.144 TFLOPS. But you only get that speed if you never read any data or write back any results or do anything else other than a multiply followed by an addition.

 

A "thread" (and Krohm rightfully warned of its use as a marketing buzzword) is generally understood to be an execution context. If a device executes a program, this refers to the current state, such as the current position in the program, the current values of the local variables, etc.

 

Threads and peak performance are two entirely different things!

 

Some compute devices (some Intel CPUs, some AMD CPUs, SUN niagara CPUs and most GPUs) can store more than one execution context aka "thread" on the chip so that they can interleave the execution of both/all of them. This sometimes falls under the term of "hardware-threads", at least for CPUs. And this is done for performance reasons. But it does not affect the theoretical peak performance of the device, only how much of that you can actually use. And the direct relationship between the maximum number of hardware threads, the used number of hardware threads, and the achieved performance ... is very complicated. It depends on lots of different factors like memory throughput, memory latency, access patterns, the actual algorithm, and so on.

So if this is what you are asking about, then you might have to look into how GPUs work and how certain algorithms make use of that.

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