In heterogeneous CPU+GPU SoCs where a single DRAM is shared between both devices, concurrent memory accesses from both devices can lead to slowdowns due to memory interference. This prevents the deployment of real-time tasks, which need to be guaranteed to complete before a set deadline. However, freedom from interference can be guaranteed through software memory scheduling, but may come at a significant cost due to frequent CPU-GPU synchronizations. In this paper we provide a compile-time model to help developers make informed decisions on how to achieve freedom from interference at the lowest cost
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
Today's heterogeneous architectures bring together multiple general purpose CPUs, domain specific GP...
none3siThe deployment of real-time workloads on commercial off-the-shelf (COTS) hardware is attracti...
In heterogeneous CPU+GPU SoCs where a single DRAM is shared between both devices, concurrent memory ...
The ever-increasing need for computational power in embedded devices has led to the adoption heterog...
Heterogeneous systems-on-A-chip are increasingly embracing shared memory designs, in which a single ...
In recent processor development, we have witnessed the in-tegration of GPU and CPUs into a single ch...
Heterogeneous systems combine general-purpose CPUs with domain-specific accelerators like GPUs. Rece...
Like most high-end embedded systems, FPGA-based systems-on-chip (SoC) are increasingly adopting hete...
<p>Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPUs are ...
Abstract—Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPU...
Most of today’s mixed criticality platforms feature Systems on Chip (SoC) where a multi-core CPU co...
<p>When multiple processor (CPU) cores and a GPU integrated together on the same chip share the off-...
Reconfigurable heterogeneous systems-on-chips (SoCs) integrating multiple accelerators are cost-effe...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
Today's heterogeneous architectures bring together multiple general purpose CPUs, domain specific GP...
none3siThe deployment of real-time workloads on commercial off-the-shelf (COTS) hardware is attracti...
In heterogeneous CPU+GPU SoCs where a single DRAM is shared between both devices, concurrent memory ...
The ever-increasing need for computational power in embedded devices has led to the adoption heterog...
Heterogeneous systems-on-A-chip are increasingly embracing shared memory designs, in which a single ...
In recent processor development, we have witnessed the in-tegration of GPU and CPUs into a single ch...
Heterogeneous systems combine general-purpose CPUs with domain-specific accelerators like GPUs. Rece...
Like most high-end embedded systems, FPGA-based systems-on-chip (SoC) are increasingly adopting hete...
<p>Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPUs are ...
Abstract—Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPU...
Most of today’s mixed criticality platforms feature Systems on Chip (SoC) where a multi-core CPU co...
<p>When multiple processor (CPU) cores and a GPU integrated together on the same chip share the off-...
Reconfigurable heterogeneous systems-on-chips (SoCs) integrating multiple accelerators are cost-effe...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
Today's heterogeneous architectures bring together multiple general purpose CPUs, domain specific GP...
none3siThe deployment of real-time workloads on commercial off-the-shelf (COTS) hardware is attracti...