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Graph processing on GPUs: A survey
In the big data era, much real-world data can be naturally represented as graphs.
Consequently, many application domains can be modeled as graph processing. Graph …
Consequently, many application domains can be modeled as graph processing. Graph …
Cloud computing landscape and research challenges regarding trust and reputation
Cloud Computing is an emerging computing paradigm. It shares massively scalable, elastic
resources (eg, data, calculations, and services) transparently among the users over a …
resources (eg, data, calculations, and services) transparently among the users over a …
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 …
Cnvlutin: Ineffectual-neuron-free deep neural network computing
This work observes that a large fraction of the computations performed by Deep Neural
Networks (DNNs) are intrinsically ineffectual as they involve a multiplication where one of …
Networks (DNNs) are intrinsically ineffectual as they involve a multiplication where one of …
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 …
GPUWattch: Enabling energy optimizations in GPGPUs
General-purpose GPUs (GPGPUs) are becoming prevalent in mainstream computing, and
performance per watt has emerged as a more crucial evaluation metric than peak …
performance per watt has emerged as a more crucial evaluation metric than peak …
Transparent offloading and map** (TOM) enabling programmer-transparent near-data processing in GPU systems
Main memory bandwidth is a critical bottleneck for modern GPU systems due to limited off-
chip pin bandwidth. 3D-stacked memory architectures provide a promising opportunity to …
chip pin bandwidth. 3D-stacked memory architectures provide a promising opportunity to …
Cache-conscious wavefront scheduling
This paper studies the effects of hardware thread scheduling on cache management in
GPUs. We propose Cache-Conscious Wave front Scheduling (CCWS), an adaptive …
GPUs. We propose Cache-Conscious Wave front Scheduling (CCWS), an adaptive …
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 …
offer a cost-effective platform for many applications by providing high thread level …
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 …
computation by exploiting abundant thread-level parallelism (TLP) offered by many classes …