April 2011
Intermediate to advanced
364 pages
10h 8m
English
Content preview from Algorithms and Parallel Computing
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
3.10 SM
A stream multiprocessor is a type of SIMD or a MIMD machine where the constituent processors are streaming processors (SPs) or thread processors. A stream processor is defined as a processor that deals with data streams, and its instruction set architecture (ISA) contains kernels to process these streams [32]. The concept of stream processing is closely associated with the graphics processing unit (GPU) where the GPU is thereby able to perform general compute-intensive general-purpose computations. The GPU thus becomes a general-purpose GPU. Examples of data streams are vectors of floating point numbers or a group of frame pixels for video data processing. This type of data shows temporal and spatial localities. Temporal locality is when the input data stream is used only a few times to produce the output steam. Spatial locality is when the input data stream is located in the same memory block. A successful example of a stream multiprocessor is the new generations of GPUs like Fermi from NVIDIA [33].
Applications suited for SM must satisfy three characteristics [34]:
1. Compute intensity
2. Data parallelism
3. Consumer–producer locality, that is, temporal and spatial locality
Compute intensity is defined as the number of arithmetic operations per I/O or global memory reference. In applications suitable for stream processing, this ratio could reach 50:1 and above. Data parallelism is when the same operation is performed on all data in an input stream in parallel. Producer–consumer ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.