In modern Commercial Off-The-Shelf (COTS) multicore systems, each core can generate many parallel memory requests at a time. The processing of these parallel requests in the DRAM controller greatly affects the memory interference delay experienced by running tasks on the platform. In this paper, we model a modern COTS multicore system which has a nonblocking last-level cache (LLC) and a DRAM controller that prioritizes reads over writes. To minimize interference, we focus on LLC and DRAM bank partitioned systems. Based on the model, we propose an analysis that computes a safe upper bound for the worst-case memory interference delay. We validated our analysis on a real COTS multicore platform with a set of carefully designed synthetic benchmarks as well as SPEC2006 benchmarks. Evaluation results show that our analysis is more accurately capture the worst-case memory interference delay and provides safer upper bounds compared to a recently proposed analysis which significantly under-estimate the delay.
Initially, many researchers model the cost to access the main memory as a constant and view the main memory as a single resource shared by the cores @cite_29 @cite_25 @cite_26 @cite_4 . However, modern DRAM systems are composed of many sophisticated components and the memory access cost is far from being a constant as it varies significant depending on the states of the variety of components comprising the system.
@cite_29 @cite_26 @cite_4 @cite_25
2054161218 2015827499 2015772022 1645807896
As main memory systems begin to face the scaling challenges from DRAM technology, future computer systems need to adapt to the emerging memory technologies like Phase-Change Memory (PCM or PRAM). While these newer technologies offer advantages such as storage density, non-volatility, and low energy consumption, they are constrained by limited write endurance that becomes more pronounced with process variation. In this paper, we propose a novel PRAM-based main memory system, RePRAM (Recycling PRAM), which leverages a group of faulty pages and recycles them in a managed way to significantly extend the PRAM lifetime while minimizing the performance impact. In particular, we explore two different dimensions of dynamic redundancy levels and group sizes, and design low-cost hardware and software support for RePRAM. Our proposed scheme involves minimal hardware modifications (that have less than 1 on-chip and off-chip area overheads). Also, our schemes can improve the PRAM lifetime by up to 43× (times) over a chip with no error correction capabilities, and outperform prior schemes such as DRM and ECP at a small fraction of the hardware cost. The performance overhead resulting from our scheme is less than 7 on average across 21 applications from SPEC2006, Splash-2, and PARSEC benchmark suites. DRAM consists of multiple resources called banks that can be accessed in parallel and independently maintain state information. In Commercial Off-The-Shelf (COTS) multicore platforms, banks are typically shared among all cores, even though programs running on the cores do not share memory space. In this situation, memory performance is highly unpredictable due to contention in the shared banks. DRAM technology challenges have increased the necessity to adapt to the emerging memory technologies like Phase-Change Memory (PCM or PRAM). While such emerging technologies provide benefits like storage density, nonvolatility, and low energy consumption, they are constrained by limited write endurance that becomes more pronounced with process variation. In this article, we explore a novel PRAM-based main memory system which resuscitates a group of faulty pages in a cost-effective manner to significantly extend the PCM main memory lifetime while minimizing the performance impact. In particular, we explore three different dimensions of dynamic redundancy levels and group sizes, and design low-cost hardware and software support for our proposed schemes. We aim to have minimal hardware modifications (that have less than 1p on-chip and off-chip area overheads). Also, our schemes can improve the PRAM lifetime by up to 105× (times) over a chip with no error correction capabilities, and outperform prior schemes such as DRM and ECP at a small fraction of the hardware cost. The performance overhead resulting from our scheme is less than 8p on average across 21 applications from SPEC2006, Splash-2, and PARSEC benchmark suites. The current main memory (DRAM) access speeds lag far behind CPU speeds. Cache memory, made of static RAM, is being used in today’s architectures to bridge this gap. It provides access latencies of 2-4 processor cycles, in contrast to main memory which requires 15-25 cycles. Therefore, the performance of the CPU depends upon how well the cache can be utilized. We show that there are significant benefits in redesigning our traditional query processing algorithms so that they can make better use of the cache. The new algorithms run 8 -200 faster than the traditional ones.