Lecture 2 â Threads - many-core.group

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What is happening on the hardware? • The <strong>core</strong>s (Scalar Processors – SPs) of the CUDA GPU are <strong>group</strong>ed into Streaming Multiprocessors – SMs – each with 8 SPs. • Each SM has 16kB of shared memory • All threads of a thread block will be scheduled on the same SM • More than one block can reside on the same SM at the same time – provided there is enough memory on the SM
Streaming multiprocessors and shared memory
Page 1 and 2: Lecture 2 - Threads Graham Pullan D
Page 3 and 4: Threads, thread blocks and shared m
Page 5 and 6: Threads • Example in L1 made no u
Page 7 and 8: Kernel for c = a + b __global__ voi
Page 9 and 10: Threads, blocks and grid Block is s
Page 11: More on thread blocks • Thread bl
Page 15 and 16: Governing equation • Heat conduct
Page 17 and 18: 2D heat conduction • In 2D: ∂T
Page 19 and 20: Domain
Page 21 and 22: Results Initial field After 50000 s
Page 23 and 24: GPU strategy 1 • Start a thread f
Page 25 and 26: GPU strategy 1 - threads and blocks
Page 27 and 28: GPU strategy 1 - kernel launch code
Page 29 and 30: Performance • CPU - 1 core, Intel
Page 31 and 32: GPU strategy 2 - threads and blocks
Page 33 and 34: GPU strategy 2 - kernel (part 1) //
Page 35 and 36: Performance • CPU - 1 core, Intel
Page 37 and 38: GPU strategy 3 • Can use larger b
Page 39 and 40: GPU strategy 3
Page 45 and 46: Lecture 2 summary

Lecture 2 â Threads - many-core.group

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Lecture 2 â Threads - many-core.group