Computer architecture simulation tools are essential for implementing and evaluating new
ideas in the domain and can be useful for understanding the behavior of programs and …

Sparse matrix-vector multiplication (SpMV) has always been a hot topic of research for
scientific computing and big data processing, but the sparsity and discontinuity of the …

Emerging Non-Volatile Memories (NVMs) have promising advantages (eg, lower idle power,
higher density, and non-volatility) over the existing predominant main memory technology …

In this paper, we introduce an accurate and scalable memory modeling framework for
General Purpose Graphics Processor units (GPGPUs), PPT-GPU-Mem. That is Performance …

One widely used metric that measures data locality is reuse distance—the number of unique
memory locations that are accessed between two consecutive accesses to a particular …

Reuse distance has been shown to be a useful metric for performance analysis of caches
and programs, locality analysis and compiler optimization. Concurrent reuse distance profile …

The processing of data-intensive applications, followed by an unprecedented amount of
data traffic, drives explosive accesses to the memory subsystem. The overloaded memory …

To mitigate the ever worsening “Power wall” and “Memory wall” problems, multi-core
architectures with multi-level cache hierarchies have been widely accepted in modern …

Cache efficiency is important to avoid unnecessary data transfers and to keep processors
active. Cache partitioning, a technique to virtually divide a cache into multiple partitions, has …

To mitigate the performance gap between CPU and the main memory, multi-level cache
architectures are widely used in modern processors. Therefore, modeling the behaviors of …