Computing systems have become increasingly heterogeneous contributing to higher performance and power efficiency. However, this is at the cost of increasing the overall complexity of designing such systems. One key challenge in the design of heterogeneous systems is the efficient scheduling of computational load. To address this challenge, this paper thoroughly analyzes state of the art scheduling policies and proposes a new dynamic scheduling heuristic: Alternative Processor within Threshold (APT). This heuristic uses a flexibility factor to attain efficient usage of the available hardware resources, taking advantage of the degree of heterogeneity of the system. In a GPU-CPU-FPGA system, tested on workloads with and without data dependenci...
none5siThis paper presents a power-aware scheduling algorithm based on efficient distribution of the...
Abstract. This work presents the application of parallel computing techniques using Graphic Processi...
A personal computer can be considered as a one-node heterogeneous cluster that simultaneously proces...
Computing systems have become increasingly heterogeneous contributing to higher performance and powe...
There has been a recent increase of interest in heterogeneous computing systems, due partly to the f...
(eng) Scheduling computational tasks on processors is a key issue for high-performance computing. Al...
With the emergence of General Purpose computation on GPU (GPGPU) and corresponding programming fram...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
Modern computing applications are becoming increasingly data-hungry and computationally expensive. T...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
(eng) Scheduling computation tasks on processors is a key issue for high-performance computing. Alth...
Scheduling computational tasks on processors is a key issue for high-performance computing. Although...
Heterogeneous architectures are currently widespread. With the advent of easy-to-program general pu...
none5siThis paper presents a power-aware scheduling algorithm based on efficient distribution of the...
Abstract. This work presents the application of parallel computing techniques using Graphic Processi...
A personal computer can be considered as a one-node heterogeneous cluster that simultaneously proces...
Computing systems have become increasingly heterogeneous contributing to higher performance and powe...
There has been a recent increase of interest in heterogeneous computing systems, due partly to the f...
(eng) Scheduling computational tasks on processors is a key issue for high-performance computing. Al...
With the emergence of General Purpose computation on GPU (GPGPU) and corresponding programming fram...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
Modern computing applications are becoming increasingly data-hungry and computationally expensive. T...
International audienceHeterogeneous architectures are currently widespread. With the advent of easy-...
(eng) Scheduling computation tasks on processors is a key issue for high-performance computing. Alth...
Scheduling computational tasks on processors is a key issue for high-performance computing. Although...
Heterogeneous architectures are currently widespread. With the advent of easy-to-program general pu...
none5siThis paper presents a power-aware scheduling algorithm based on efficient distribution of the...
Abstract. This work presents the application of parallel computing techniques using Graphic Processi...
A personal computer can be considered as a one-node heterogeneous cluster that simultaneously proces...