The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Workshop:MCHPC’20: Workshop on Memory Centric High-Performance Computing
Authors: Yifan Qiao (Rensselaer Polytechnic Institute); Xubin Chen, Jingpeng Hao, and Tong Zhang (Rensselaer Polytechnic Institute (RPI)); and Changsheng Xie and Fei Wu (Huazhong University of Science & Technology)
Abstract: This paper advocates a DRAM-only design strategy to reduce the computing system memory cost and demonstrates its potential in the context of relational database. In particular, we envision a low-cost heterogeneous DRAM fabric consisting of convenient but expensive byte-addressable DRAM and large-capacity low-cost DRAM with coarse access granularity (e.g., 1K-byte). Regardless of specific memory technology, one can reduce the manufacturing cost by sacrificing the memory raw reliability, and apply error correction code~(ECC) to restore the data storage integrity. The efficiency of ECC significantly improves as the codeword length increases, which enlarges the memory access granularity. This leads to a fundamental trade-off between memory cost and access granularity. Following this principle, Intel 3DXP-based Optane memory DIMM internally operates with a 256-byte ECC codeword length (hence 256-byte access granularity), and Hynix recently demonstrated low-cost DRAM DIMM with a 64-byte access granularity. This paper presents a design approach that enables relational database to take full advantage of the envisioned low-cost heterogeneous DRAM fabric to improve performance with only minimal database source code modification. Using MySQL as a test vehicle, we implemented a prototyping system, on which we have demonstrated its effectiveness under TPC-C and Sysbench OLTP benchmarks.
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