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 …
Accel-Sim: An extensible simulation framework for validated GPU modeling
In computer architecture, significant innovation frequently comes from industry. However, the
simulation tools used by industry are often not released for open use, and even when they …
simulation tools used by industry are often not released for open use, and even when they …
Transparent offloading and mapping (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 …
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 …
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 …
Simultaneous multikernel GPU: Multi-tasking throughput processors via fine-grained sharing
Studies show that non-graphics programs can be less optimized for the GPU hardware,
leading to significant resource under-utilization. Sharing the GPU among multiple programs …
leading to significant resource under-utilization. Sharing the GPU among multiple programs …
Mosaic: a GPU memory manager with application-transparent support for multiple page sizes
R Ausavarungnirun, J Landgraf, V Miller… - Proceedings of the 50th …, 2017 - dl.acm.org
Contemporary discrete GPUs support rich memory management features such as virtual
memory and demand paging. These features simplify GPU programming by providing a …
memory and demand paging. These features simplify GPU programming by providing a …
Improving GPGPU resource utilization through alternative thread block scheduling
High performance in GPGPU workloads is obtained by maximizing parallelism and fully
utilizing the available resources. The thousands of threads are assigned to each core in …
utilizing the available resources. The thousands of threads are assigned to each core in …
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 …