A survey of methods for analyzing and improving GPU energy efficiency
Recent years have witnessed phenomenal growth in the computational capabilities and
applications of GPUs. However, this trend has also led to a dramatic increase in their power …
applications of GPUs. However, this trend has also led to a dramatic increase in their power …
A survey of power and energy predictive models in HPC systems and applications
Power and energy efficiency are now critical concerns in extreme-scale high-performance
scientific computing. Many extreme-scale computing systems today (for example: Top500) …
scientific computing. Many extreme-scale computing systems today (for example: Top500) …
A reconfigurable fabric for accelerating large-scale datacenter services
Datacenter workloads demand high computational capabilities, flexibility, power efficiency,
and low cost. It is challenging to improve all of these factors simultaneously. To advance …
and low cost. It is challenging to improve all of these factors simultaneously. To advance …
A reconfigurable fabric for accelerating large-scale datacenter services
To advance datacenter capabilities beyond what commodity server designs can provide, the
authors designed and built a composable, reconfigurable fabric to accelerate large-scale …
authors designed and built a composable, reconfigurable fabric to accelerate large-scale …
A reconfigurable fabric for accelerating large-scale datacenter services
Datacenter workloads demand high computational capabilities, flexibility, power efficiency,
and low cost. It is challenging to improve all of these factors simultaneously. To advance …
and low cost. It is challenging to improve all of these factors simultaneously. To advance …
Map-reduce processing of k-means algorithm with FPGA-accelerated computer cluster
YM Choi, HKH So - 2014 IEEE 25th international conference …, 2014 - ieeexplore.ieee.org
The design and implementation of the k-means clustering algorithm on an FPGA-
accelerated computer cluster is presented. The implementation followed the Map-Reduce …
accelerated computer cluster is presented. The implementation followed the Map-Reduce …
A model for distributed in-network and near-edge computing with heterogeneous hardware
RA Cooke, SA Fahmy - Future Generation Computer Systems, 2020 - Elsevier
Applications that involve analysis of data from distributed networked data sources typically
involve computation performed centrally in a datacenter or cloud environment, with some …
involve computation performed centrally in a datacenter or cloud environment, with some …
R3TOS: a novel reliable reconfigurable real-time operating system for highly adaptive, efficient, and dependable computing on FPGAs
Despite the clear potential of FPGAs to push the current power wall beyond what is possible
with general-purpose processors, as well as to meet ever more exigent reliability …
with general-purpose processors, as well as to meet ever more exigent reliability …
[HTML][HTML] A full-parallel implementation of Self-Organizing Maps on hardware
Abstract Self-Organizing Maps (SOMs) are extensively used for data clustering and
dimensionality reduction. However, if applications are to fully benefit from SOM based …
dimensionality reduction. However, if applications are to fully benefit from SOM based …
Parallel implementation of k-means algorithm on fpga
The K-means algorithm is widely used to find correlations between data in different
application domains. However, given the massive amount of data stored, known as Big …
application domains. However, given the massive amount of data stored, known as Big …