Title: Improving DRAM Performance by Parallelizing Refreshes with Accesses

Kevin Chang

Tuesday, Mar. 25th, 4:00pm-5:00pm
Hamerschlag Hall D-210

Abstract

Modern DRAM cells are periodically refreshed to prevent data loss due to

leakage. Commodity DRAM refreshes cells at the rank level. This degrades

performance significantly because it prevents an entire DRAM rank from serving

memory requests while being refreshed. We propose two new complementary

techniques, DARP (Dynamic Access Refresh Parallelization) and SARP (Subarray

Access Refresh Parallelization), to mitigate the DRAM refresh penalty

by enhancing refresh-access parallelization at the bank and subarray levels,

respectively. DARP 1) issues per-bank refreshes to idle banks in an

out-of-order manner instead of issuing refreshes in a strict round-robin

order, 2) proactively schedules per-bank refreshes during intervals when a

batch of writes are draining to DRAM. SARP enables a bank to serve requests

from idle subarrays in parallel with other subarrays that are being refreshed.

Extensive evaluations on a wide variety of workloads and systems show that our

mechanisms improve system performance (and energy efficiency) compared to

state-of-the-art refresh policies.

Bio

Kevin Chang is a third year PhD student in the Electrical and Computer

Engineering Department at Carnegie Mellon University, where he is advised by

Professor Onur Mutlu. His research focuses on improving performance and

energy-efficiency of memory sub-systems. He has also done work in the past on

high-performance on-chip interconnects. He received his B.S./M.S. in Electrical

and Computer Engineering in 2011.