The emerging many integrated core architecture (MIC) Xeon Phi coprocessor becomes the mainstream platform for high performance computing. For database applications, in-memory analytics requires computation intensive workload in which the in-memory foreign key joins between big fact table and dimension tables dominate the OLAP performance. This paper focuses on a cache-friendly foreign key join with respect to cache-conscious radix partitioning oriented hash join and cache-oblivious no-partitioning hash join to adapt to the small LLC size and massive simultaneous multi-threading mechanism of Xeon Phi coprocessor. By exploiting the characteristic of surrogate key in OLAP schema, the key matching oriented hash probing can be further simplified as surrogate key referencing between fact table and dimension tables with PK-FK reference constraint, so that the complex hash table and CPU cycle consuming hash probing can be simplified as directly referencing surrogate vector by mapping foreign key to offset address of surrogate vector. The surrogate vector referencing oriented foreign key join is simple and efficient to be implemented for Xeon Phi coprocessor for more cores, and also offers massive simultaneous multi-threading mechanism to overlap memory access latency. In experiments, the surrogate vector referencing foreign key join algorithm and traditional hash join algorithms (NPO and PRO) are compared on both Xeon E5-2650 v3 10-core CPU platform and Xeon Phi 5110P 60-core platform, the experimental results provide a comprehensive perspective for how the mainstream in-memory foreign key join algorithms perform with different datasets on different platforms.