Landrush: Rethinking in-situ analysis for gpgpu workflows
In-situ analysis on the output data of scientific simulations has been made necessary by ever-
growing output data volumes and increasing costs of data movement as supercomputing is …
growing output data volumes and increasing costs of data movement as supercomputing is …
Understanding performance-quality trade-offs in scientific visualization workflows with lossy compression
The cost of I/O is a significant challenge on current supercomputers, and the trend is likely to
continue into the foreseeable future. This challenge is amplified in scientific visualization …
continue into the foreseeable future. This challenge is amplified in scientific visualization …
Smart-io: System-aware two-level data organization for efficient scientific analytics
Current I/O techniques have pushed the write performance close to the system peak, but
they usually overlook the read side of problem. With the mounting needs of scientific …
they usually overlook the read side of problem. With the mounting needs of scientific …
Mitigating gpu memory divergence for data-intensive applications
B Wang - 2015 - search.proquest.com
Abstract Graphics Processing Units (GPUs) have proven as a viable technology for a wide
variety of general purpose applications to exploit the massive computing capability and high …
variety of general purpose applications to exploit the massive computing capability and high …
Enhancing manageability of execution and data for GPGPU computing
A Goswami - 2016 - repository.gatech.edu
GPGPUs are useful for many types of compute-intensive workloads from scientific
simulations to cloud-focused applications like machine learning and graph analytics …
simulations to cloud-focused applications like machine learning and graph analytics …