Deep learning (DL) systems suffer from low resource utilization due to 1) monolithic server
model that tightly couples compute and memory; and 2) limited sharing between different …

We introduce EasyIO, a new approach to explore asynchronous I/O on filesystems designed
for (disaggregated) nonvolatile memories to improve CPU efficiency. EasyIO offloads …

Non-volatile memory (NVM) opens up new opportunities to resolve scaling restrictions of
main memory, yet it is still hindered by the write disturbance (WD) problem. The WD problem …

In contemporary database applications, the demand for memory resources is intensively
high. To enhance adaptability to varying resource needs and improve cost efficiency, the …

Despite being a powerful concept, distributed shared memory (DSM) has not been made
practical due to the extensive synchronization needed between servers to implement …

Hybrid main memory systems combine both performance and capacity advantages from
heterogeneous memory technologies. With larger capacities, higher associativities, and finer …

In distributed systems, tuple space is one of the coordination models that significantly
maximizes system performance against failure due to its space and time decoupling …

Datacenters of today have maintained the same architecture for decades using the server as
the primary building block. However, this traditional approach suffers from under-utilization …

With an explosive increase of data produced annually, researchers have been attempting to
develop solutions for systems that can effectively handle large amounts of data. Single …

Resource disaggregation has emerged as a promising solution to enhance both resource
utilization and management efficiency in datacenters. Existing disaggregation solutions …