A load balancing technique for memory channels
Byoungchan Oh, Nam Sung Kim, Jeongseob Ahn, Bingchao Li, Ronald Dreslinski, Trevor Mudge · Proceedings of the International Symposium on Memory Systems · 2018
The performance needs of memory systems caused by growing volumes of data from emerging applications, such as machine learning and big data analytics, have continued to increase. As a result, HBM has been introduced in GPUs and throughput oriented processors. HBM is a stack of multiple DRAM devices across a number of memory channels. Although HBM provides a large number of channels and high peak bandwidth, we observed that all channels are not evenly utilized and often only one or few channels are highly congested after applying the hashing technique to randomize the translated physical memory address.