A modern primer on processing in memory
Modern computing systems are overwhelmingly designed to move data to computation. This
design choice goes directly against at least three key trends in computing that cause …
design choice goes directly against at least three key trends in computing that cause …
Processing data where it makes sense: Enabling in-memory computation
Today's systems are overwhelmingly designed to move data to computation. This design
choice goes directly against at least three key trends in systems that cause performance …
choice goes directly against at least three key trends in systems that cause performance …
Near-memory computing: Past, present, and future
The conventional approach of moving data to the CPU for computation has become a
significant performance bottleneck for emerging scale-out data-intensive applications due to …
significant performance bottleneck for emerging scale-out data-intensive applications due to …
Syncron: Efficient synchronization support for near-data-processing architectures
Near-Data-Processing (NDP) architectures present a promising way to alleviate data
movement costs and can provide significant performance and energy benefits to parallel …
movement costs and can provide significant performance and energy benefits to parallel …
Performance optimization for edge-cloud serverless platforms via dynamic task placement
We present a framework for performance optimization in serverless edge-cloud platforms
using dynamic task placement. We focus on applications for smart edge devices, for …
using dynamic task placement. We focus on applications for smart edge devices, for …
Understanding and improving the latency of DRAM-based memory systems
KK Chang - 2017 - search.proquest.com
Over the past two decades, the storage capacity and access bandwidth of main memory
have improved tremendously, by 128x and 20x, respectively. These improvements are …
have improved tremendously, by 128x and 20x, respectively. These improvements are …
Revisiting the design of data stream processing systems on multi-core processors
Driven by the rapidly increasing demand for handling real-time data streams, many data
stream processing (DSP) systems have been proposed. Regardless of the different …
stream processing (DSP) systems have been proposed. Regardless of the different …
Runtime object lifetime profiler for latency sensitive big data applications
Latency sensitive services such as credit-card fraud detection and website targeted
advertisement rely on Big Data platforms which run on top of memory managed runtimes …
advertisement rely on Big Data platforms which run on top of memory managed runtimes …
Improving spark application throughput via memory aware task co-location: A mixture of experts approach
Data analytic applications built upon big data processing frameworks such as Apache Spark
are an important class of applications. Many of these applications are not latency-sensitive …
are an important class of applications. Many of these applications are not latency-sensitive …
BDEv 3.0: energy efficiency and microarchitectural characterization of Big Data processing frameworks
As the size of Big Data workloads keeps increasing, the evaluation of distributed frameworks
becomes a crucial task in order to identify potential performance bottlenecks that may delay …
becomes a crucial task in order to identify potential performance bottlenecks that may delay …