By utilizing diverse heterogeneous hardware resources, developers can significantly
improve the performance of their applications. Currently, in order to determine which parts of …

Heterogeneous architectures are vastly used in various high performance computing
systems from IoT‐based embedded architectures to edge and cloud systems. Although …

Heterogeneous platforms composed of multiple different types of computing devices (such
as CPUs, GPUs, and Intel MICs) have been widely used recently. However, most of parallel …

The problem of scheduling of workloads onto heterogeneous processors (eg, CPUs, GPUs,
FPGAs) is of fundamental importance in modern data centers. Current system schedulers …

Datacenter servers are increasingly heterogeneous: from x86 host CPUs, to ARM or RISC-V
CPUs in NICs/SSDs, to FPGAs. Previous works have demonstrated that migrating …

The subject technology runs a compiled neural network (NN) model on a particular
processor with multiple priority queues for executing different processes, the compiled NN …

Heterogeneous-ISA processor designs have attracted considerable research interest.
However, unlike their homogeneous-ISA counterparts, explicit software support for bridging …

Large-scale computing systems rely on many control and decision-making algorithms.
Classical approaches to designing and optimizing these algorithms are poorly suited to the …

As device and voltage scaling cease, ever-increasing performance targets can only be
achieved through the design of parallel, heterogeneous architectures. The workloads …