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Articles by Intel ISN (Articles: 8)

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Posted: 1 Apr 2010   Updated: 1 Apr 2010   Views: 11,594   Rating: 0.0 / 5    Votes: 0   Popularity: 0.0
Licence: The Code Project Open License (CPOL)      Bookmarked: 12   Downloaded: 0
In data-parallel applications, the same independent operation is performed repeatedly on different data. Loops are usually the most compute-intensive segments of data parallel applications, so loop optimizations directly impact performance.
Posted: 8 Apr 2010   Updated: 8 Apr 2010   Views: 7,066   Rating: 5.00/5    Votes: 3   Popularity: 2.39
Licence: The Code Project Open License (CPOL)      Bookmarked: 6   Downloaded: 0
One key to attaining good parallel performance is choosing the right granularity for the application. The goal is to determine the right granularity (usually larger is better) for parallel tasks, while avoiding load imbalance and communication overhead to achieve the best performance.
Posted: 8 Apr 2010   Updated: 8 Apr 2010   Views: 13,447   Rating: 5.00/5    Votes: 5   Popularity: 3.49
Licence: The Code Project Open License (CPOL)      Bookmarked: 17   Downloaded: 0
Load balancing an application workload among threads is critical to performance. However, achieving perfect load balance is non-trivial, and it depends on the parallelism within the application, workload, the number of threads, load balancing policy, and the threading implementation.
Posted: 8 Apr 2010   Updated: 8 Apr 2010   Views: 4,538   Rating: 5.00/5    Votes: 1   Popularity: 0.00
Licence: The Code Project Open License (CPOL)      Bookmarked: 4   Downloaded: 0
Many applications and algorithms contain serial optimizations that inadvertently introduce data dependencies and inhibit parallelism. One can often remove such dependences through simple transforms, or even avoid them altogether through techniques such as domain decomposition or blocking.
Posted: 2 Jun 2010   Updated: 2 Jun 2010   Views: 4,225   Rating: 0.0 / 5    Votes: 0   Popularity: 0.0
Licence: The Code Project Open License (CPOL)      Bookmarked: 2   Downloaded: 0
Many compute-intensive applications involve complex transformations of ordered input data to ordered output data. While the algorithms employed in these transformations are often parallel, managing the I/O order dependence can be a challenge.
Posted: 2 Jun 2010   Updated: 2 Jun 2010   Views: 6,754   Rating: 0.0 / 5    Votes: 0   Popularity: 0.0
Licence: The Code Project Open License (CPOL)      Bookmarked: 4   Downloaded: 0
Allocating memory from the system heap can be an expensive operation due to a lock used by system runtime libraries to synchronize access to the heap. Contention on this lock can limit the performance benefits from multithreading. Learn how to solve this problem.
Posted: 2 Jun 2010   Updated: 2 Jun 2010   Views: 9,912   Rating: 4.00/5    Votes: 1   Popularity: 0.00
Licence: The Code Project Open License (CPOL)      Bookmarked: 6   Downloaded: 0
Synchronization is often an expensive operation that can limit the performance of a multithreaded program. Using thread-local data structures instead of data structures shared by the threads can reduce synchronization in certain cases, allowing a program to run faster.
Posted: 2 Jun 2010   Updated: 2 Jun 2010   Views: 6,252   Rating: 5.00/5    Votes: 2   Popularity: 1.51
Licence: The Code Project Open License (CPOL)      Bookmarked: 2   Downloaded: 0
In symmetric multiprocessor (SMP) systems, each processor has a local cache. The memory system must guarantee cache coherence. False sharing occurs when threads on different processors modify variables that reside on the same cache line. Learn methods to detect and correct false sharing.
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Intel ISN

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