OWL: cooperative thread array aware scheduling techniques for improving GPGPU performance
Emerging GPGPU architectures, along with programming models like CUDA and OpenCL,
offer a cost-effective platform for many applications by providing high thread level parallelism …
offer a cost-effective platform for many applications by providing high thread level parallelism …
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation
challenge providing training and test data to registered participants. The training data …
challenge providing training and test data to registered participants. The training data …
Cache revive: Architecting volatile STT-RAM caches for enhanced performance in CMPs
High density, low leakage and non-volatility are the attractive features of Spin-Transfer-Torque-RAM
(STT-RAM), which has made it a strong competitor against SRAM as a universal …
(STT-RAM), which has made it a strong competitor against SRAM as a universal …
[HTML][HTML] MRBrainS challenge: online evaluation framework for brain image segmentation in 3T MRI scans
Many methods have been proposed for tissue segmentation in brain MRI scans. The
multitude of methods proposed complicates the choice of one method above others. We have …
multitude of methods proposed complicates the choice of one method above others. We have …
Neither more nor less: Optimizing thread-level parallelism for GPGPUs
General-purpose graphics processing units (GPG-PUs) are at their best in accelerating
computation by exploiting abundant thread-level parallelism (TLP) offered by many classes of …
computation by exploiting abundant thread-level parallelism (TLP) offered by many classes of …
Orchestrated scheduling and prefetching for GPGPUs
In this paper, we present techniques that coordinate the thread scheduling and prefetching
decisions in a General Purpose Graphics Processing Unit (GPGPU) architecture to better …
decisions in a General Purpose Graphics Processing Unit (GPGPU) architecture to better …
Scheduling techniques for GPU architectures with processing-in-memory capabilities
Processing data in or near memory (PIM), as opposed to in conventional computational units
in a processor, can greatly alleviate the performance and energy penalties of data transfers …
in a processor, can greatly alleviate the performance and energy penalties of data transfers …
Random forest regression for magnetic resonance image synthesis
By choosing different pulse sequences and their parameters, magnetic resonance imaging (MRI)
can generate a large variety of tissue contrasts. This very flexibility, however, can yield …
can generate a large variety of tissue contrasts. This very flexibility, however, can yield …
Managing GPU concurrency in heterogeneous architectures
… We run representative GPU applications alongside omnetpp on the CPU side,6 and … , we
run until the slowest core reaches 5 million instructions. To measure GPU performance, we run …
run until the slowest core reaches 5 million instructions. To measure GPU performance, we run …
Anatomy of gpu memory system for multi-application execution
As GPUs make headway in the computing landscape spanning mobile platforms,
supercomputers, cloud and virtual desktop platforms, supporting concurrent execution of multiple …
supercomputers, cloud and virtual desktop platforms, supporting concurrent execution of multiple …