Heterogeneous many-cores are now an integral part of modern computing systems ranging
from embedding systems to supercomputers. While heterogeneous many-core design offers …

Abstract Graphical Processing Unit provides massive parallelism due to the presence of
hundreds of cores. Usage of GPUs for general purpose computation (GPGPU) has resulted …

Typically, the execution time of a kernel on a GPU is a difficult to predict measure as it
depends on a wide range of factors. Performance can be limited by either memory transfer …

Performance prediction of GPU kernels is generally a tedious procedure with unpredictable
results. In this paper, we provide a practical model for estimating performance of CUDA …

Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow
software to exploit spatial and temporal sharing of computing resources to improve the …

We have designed and implemented a Grid RPC system called OmniRPC, for parallel
programming in cluster and grid environments. While OmniRPC inherits its API from Ninf, the …

Dense linear algebra operations appear very frequently in high-performance computing
(HPC) applications, rendering their performance crucial to achieve optimal scalability. As …

Abstract The Graphics Processing Unit (GPU) is a promising platform to implement Deep
Packet Inspection (DPI) due to the GPU's rich parallelism and programmability for high …

Matrix transposition is an important algorithmic building block for many numeric algorithms
such as FFT. It has also been used to convert the storage layout of arrays. With more and …

This paper aims to design an online, low-latency, and high-performance speech recognition
system using a bidirectional long short-term memory (BLSTM) acoustic model. To achieve …