Minerva: Accelerating Data Analysis in Next-Generation SSDs

Abstract

Emerging non-volatile memory (NVM) technologies have DRAM-like latency with storage-like density, offering unique capability to analyze large data sets significantly faster than flash or disk storage. However, the hybrid nature of these NVM technologies such as phase-change memory (PCM) make it difficult to use them to best advantage in the memory-storage hierarchy. These NVMs lack the fast write latency required of DRAM and are thus not suitable as DRAM equivalent on the memory bus, yet their low latency even in random access patterns is not easily exploited over an I/O bus. In this work, we describe an FPGA-based system to execute application-specific operations in the NVM controller and evaluate its performance on two microbenchmarks and a keyvalue store. Our system Minerva1extends the conventional solidstate drive (SSD) architecture to offload data or I/O intensive application code to the SSD to exploit the low latency and high internal bandwidth of NVMs. Performing computation in the FPGA-based NVM storage controller significantly reduces data traffic between the host and storage and serves as an offload engine for data analysis workloads. A runtime library enables the programmer to offload computations to the SSD without dealing with the complications of the underlying architecture and inter-controller communication management. We have implemented a prototype of Minerva on the BEE3 FPGA system. We compare the performance of Minerva to a state of the art PCIe-attached PCM-based SSD. Minerva improves performance by an order of magnitude on two microbenchmarks. Minerva based key-value store performs up to 5.2 M get operations/s and 4.0 M set operations/s which is 7.45× and 9.85× higher than the PCM-based SSD that uses the conventional I/O architecture. This huge improvement comes from the reduction of data transfer between the storage to the host and the FPGA-based data processing in the SSD.