Tag Archives: list

Parallel Sort & Reverse Algorithms of PTL Array vs. .NET List

The next video in our Parallel Template Library (PTL) video series is our “Parallel Sort and Reverse in PTL Algorithms” video. PTL differs from the .NET standard library because its Array and Iterator Algorithms components offer parallel versions of many useful algorithms, which take advantage of multicore processors to greatly improve their performance.

In this video, we demonstrate the performance of PTL’s Sort and Reverse algorithms for large data sets (1 billion elements) using a .NET List and a PTLArray container. On a quad-core processor, PTL’s parallel Sort was 4.5 times faster than the sequential Sort of the .NET List, and PTL’s parallel Reverse was 109 times faster than the sequential Reverse of the .NET List.

We executed our demo application on a system with one Intel Core i7 processor with 4 physical cores (8 logical cores with hyperthreading) and 32 GB of memory. We also restarted the demo application after each test to run each test independently and get a fair comparison.

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Memory Management of .NET List vs. PTL List64 (Video)

We continue our Parallel Template Library (PTL) video series with our “Memory Management in PTL Containers” video. The PTL Containers component for .NET and Java offers powerful data containers that have been optimized for large data sets and for parallelism to take advantage of multicore processors.

In this video, we demonstrate how PTL’s superior container architecture results in better memory management and increased performance. We compare a .NET List to a PTL List64 container. We add from 100 million to 1.1 billion elements to both containers to show how PTL uses memory much more efficiently. We also retrieve all elements from both containers to prove that random access performance was not sacrificed to implement PTL’s superior memory management scheme.

We executed our demo application on a system with one Intel Core i7 processor with 4 physical cores (8 logical cores with hyperthreading) and 32 GB of memory. We also restarted the demo application after each test to run each test independently and get a fair comparison.

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