The energy consumption of DRAM is a critical concern in modern computing systems.
Improvements in manufacturing process technology have allowed DRAM vendors to lower …

The memory system is a fundamental performance and energy bottleneck in almost all
computing systems. Recent system design, application, and technology trends that require …

DRAM latency continues to be a critical bottleneck for system performance. In this work, we
develop a low-cost mechanism, called Charge Cache, that enables faster access to recently …

Approximate computing explores opportunities that emerge when applications can tolerate
error or inexactness. These applications, which range from multimedia processing to …

This paper analyzes the trade-offs in architecting stacked DRAM either as part of main
memory or as a hardware-managed cache. Using stacked DRAM as part of main memory …

Memory devices represent a key component of datacenter total cost of ownership (TCO),
and techniques used to reduce errors that occur on these devices increase this cost. Existing …

Systems from smartphones to supercomputers are increasingly heterogeneous, being
composed of both CPUs and GPUs. To maximize cost and energy efficiency, these systems …

As the scaling of applications increases, the demand of main memory capacity increases in
order to serve large working set. It is difficult for DRAM (dynamic random access memory) …

While the memory footprints of cloud and HPC applications continue to increase,
fundamental issues with DRAM scaling are likely to prevent traditional main memory …

Modern data-parallel systems such as Spark rely increasingly on in-memory computing that
can significantly improve the efficiency of iterative algorithms. To process real-world …