Intel threading building blocks : outfitting C++ for multi-core processor parallelism
- Authors
- James Reinders
In The Last Decade
doi.org/w5246274 →Countries where authors are citing Intel threading building blocks : outfitting C++ for multi-core processor parallelism
This map shows the geographic impact of Intel threading building blocks : outfitting C++ for multi-core processor parallelism. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Intel threading building blocks : outfitting C++ for multi-core processor parallelism with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Intel threading building blocks : outfitting C++ for multi-core processor parallelism more than expected).
Fields of papers citing Intel threading building blocks : outfitting C++ for multi-core processor parallelism
This network shows the impact of Intel threading building blocks : outfitting C++ for multi-core processor parallelism. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Intel threading building blocks : outfitting C++ for multi-core processor parallelism.
About Intel threading building blocks : outfitting C++ for multi-core processor parallelism
This paper, published in 2007, received 431 indexed citations . Written by James Reinders covering the research area of Hardware and Architecture and Computer Networks and Communications. It is primarily cited by scholars working on Hardware and Architecture (318 citations), Computer Networks and Communications (305 citations), Information Systems (105 citations), Computer Vision and Pattern Recognition (46 citations) and Artificial Intelligence (43 citations).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/w5246274.