high_scalability high_scalability-2009 high_scalability-2009-636 knowledge-graph by maker-knowledge-mining
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Introduction: InfoQueue has this excellent talk by Brian Goetz on the new features being added to Java SE 7 that will allow programmers to fully exploit our massively multi-processor future. While the talk is about Java it's really more general than that and there's a lot to learn here for everyone. Brian starts with a short, coherent, and compelling explanation of why programmers can't expect to be saved by ever faster CPUs and why we must learn to exploit the strengths of multiple core computers to make our software go faster. Some techniques for exploiting multiple cores are given in an equally short, coherent, and compelling explanation of why divide and conquer as the secret to multi-core bliss, fork-join, how the Java approach differs from map-reduce, and lots of other juicy topics. The multi-core "problem" is only going to get worse. Tilera founder Anant Agarwal estimates by 2017 embedded processors could have 4,096 cores, server CPUs might have 512 cores and desktop chips could use
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1 Brian starts with a short, coherent, and compelling explanation of why programmers can't expect to be saved by ever faster CPUs and why we must learn to exploit the strengths of multiple core computers to make our software go faster. [sent-3, score-0.465]
2 Some techniques for exploiting multiple cores are given in an equally short, coherent, and compelling explanation of why divide and conquer as the secret to multi-core bliss, fork-join, how the Java approach differs from map-reduce, and lots of other juicy topics. [sent-4, score-0.815]
3 Tilera founder Anant Agarwal estimates by 2017 embedded processors could have 4,096 cores, server CPUs might have 512 cores and desktop chips could use 128 cores. [sent-6, score-0.397]
4 Some disagree saying this is too optimistic, but Agarwal maintains the number of cores will double every 18 months. [sent-7, score-0.418]
5 The number of cores is increasing so applications must now search for fine grain parallelism (fork-join) As hardware becomes more parallel, more and more cores, software has to look for techniques to find more and more parallelism to keep the hardware busy. [sent-13, score-1.187]
6 Allowed programmers to be lazy because a faster processor would be released that saved your butt. [sent-15, score-0.327]
7 So more processing power could be put on a chip which leads to putting more and more processing cores on a chip. [sent-30, score-0.45]
8 The number of cores will grow at exponential rate for the next 10 years. [sent-33, score-0.418]
9 The problem is it's harder to make a program go faster on a multicore system. [sent-38, score-0.474]
10 If you have a 100 cores you program won't go faster unless you explicitly design it to take advantage of those chips. [sent-40, score-0.595]
11 Must now be able to partition your program so it can run faster by running on multiple cores. [sent-42, score-0.282]
12 And you must be able keep doing that as the number of cores keeps improving. [sent-43, score-0.492]
13 Started off with course grain tasks which was sufficient given the number of cores. [sent-46, score-0.345]
14 This approach won't work as the number cores increase. [sent-47, score-0.508]
15 The course grained threading approach is to use a thread pool, divide up the numbers, and let the task pool compute the sub problems. [sent-59, score-0.996]
16 A shared task pool is slow as the number increases which forces the work to be more course grained. [sent-60, score-0.429]
17 Had to decide up front how many pieces to divide the problem into. [sent-65, score-0.314]
18 The fork-join pool is optimized for fine grained operations whereas the thread pool is optimized for course grained operations. [sent-77, score-0.93]
19 This approach scales nearly linearly with the number of hardware threads. [sent-81, score-0.277]
20 The goal for fork-join: Avoid context switches; Have as many threads as hardware threads and keep them all busy; Minimize queue lock contention for data structures. [sent-82, score-0.438]
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