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ASSASIN: Architecture Support for Stream Computing to Accelerate Computational Storage
Computational storage adds computing to storage devices, providing potential benefits in offload, data-reduction, and lower energy. Successful computational SSD architectures should match growing flash bandwidth, which in turn requires high SSD DRAM memory bandwidth. This creates a memory wall scaling problem, resulting from SSDs’ stringent power and cost constraints.
A survey of recent computational SSD research shows that many computational storage offloads are suited to stream computing. To exploit this opportunity, we propose a novel general-purpose computational SSD and core architecture, called ASSASIN (Architecture Support for Stream computing to Accelerate computatIoNal Storage). ASSASIN provides a unified set of compute engines between SSD DRAM and the flash array. This eliminates the SSD DRAM bottleneck by enabling direct computing on flash data streams. ASSASIN further employs a crossbar to achieve performance even when flash data layout is uneven and preserve independence for page layout decisions in the flash translation layer. With stream buffers and scratchpad memories, ASSASIN core’s memory hierarchy and instruction set extensions provide superior low-latency access at low-power and effectively keep streaming flash data out of the in-SSD cache-DRAM memory hierarchy, thereby solving the memory wall.
Evaluation shows that ASSASIN delivers 1.5x - 2.4x speedup for offloaded functions compared to state-of-the-art computational SSD architectures. Further, ASSASIN’s streaming approach yields 2.0x power efficiency and 3.2x area efficiency improvement. And these performance benefits at the level of computational SSDs translate to 1.1x - 1.5x end-to-end speedups on data analytics workloads.
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- Award ID(s):
- 1909364
- NSF-PAR ID:
- 10376847
- Date Published:
- Journal Name:
- 55th IEEE/ACM International Symposium on Microarchitecture
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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