相关论文: OpenCL + OpenSHMEM Hybrid Programming Model for th…

This paper reports the implementation and performance evaluation of the OpenSHMEM 1.3 specification for the Adapteva Epiphany architecture within the Parallella single-board computer. The Epiphany architecture exhibits massive many-core…

The energy-efficient Adapteva Epiphany architecture exhibits massive many-core scalability in a physically compact 2D array of RISC cores with a fast network-on-chip (NoC). With fully divergent cores capable of MIMD execution, the physical…

The Adapteva Epiphany many-core architecture comprises a 2D tiled mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. It offers high computational energy efficiency for both integer and floating point…

In the construction of exascale computing systems energy efficiency and power consumption are two of the major challenges. Low-power high performance embedded systems are of increasing interest as building blocks for large scale high-…

The energy-efficient Adapteva Epiphany architecture exhibits massive many-core scalability in a physically compact 2D array of RISC cores with a fast network-on-chip (NoC). The architecture presents many features and constraints which…

The Adapteva Epiphany many-core architecture comprises a scalable 2D mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. Whereas such a processor offers high computational energy efficiency and parallel…

The Epiphany is a many-core, low power, low on-chip memory architecture and one can very cheaply gain access to a number of parallel cores which is beneficial for HPC education and prototyping. The very low power nature of these…

In this paper we use the Adapteva Epiphany manycore chip to demonstrate how the throughput and the latency of a baseband signal processing chain, typically found in LTE or WiFi, can be optimized by a combination of task- and data…

The Parallella is a hybrid computing platform that came into existence as the result of a Kickstarter project by Adapteva. It is composed of the high performance, energy-efficient, manycore architecture, Epiphany chip (used as co-processor)…

In this paper we introduce Epiphany as a high-performance energy-efficient manycore architecture suitable for real-time embedded systems. This scalable architecture supports floating point operations in hardware and achieves 50 GFLOPS/W in…

Modern high-end systems are increasingly becoming heterogeneous, providing users options to use general purpose Graphics Processing Units (GPU) and other accelerators for additional performance. High Performance Computing (HPC) and…

Micro-core architectures combine many low memory, low power computing cores together in a single package. These are attractive for use as accelerators but due to limited on-chip memory and multiple levels of memory hierarchy, the way in…

This paper presents a comparison of OpenMP and OpenCL based on the parallel implementation of algorithms from various fields of computer applications. The focus of our study is on the performance of benchmark comparing OpenMP and OpenCL. We…

Deploying large language models (LLMs) for online inference is often constrained by limited GPU memory, particularly due to the growing KV cache during auto-regressive decoding. Hybrid GPU-CPU execution has emerged as a promising solution…

The electrical and electronic engineering has used parallel programming to solve its large scale complex problems for performance reasons. However, as parallel programming requires a non-trivial distribution of tasks and data, developers…

As the hardware industry moves towards using specialized heterogeneous many-cores to avoid the effects of the power wall, software developers are finding it hard to deal with the complexity of these systems. This article shares our…

The widespread adoption of LLMs has driven an exponential rise in their deployment, imposing substantial demands on inference clusters. These clusters must handle numerous concurrent queries for different LLM downstream tasks. To handle…

In this paper, we propose LoopLynx, a scalable dataflow architecture for efficient LLM inference that optimizes FPGA usage through a hybrid spatial-temporal design. The design of LoopLynx incorporates a hybrid temporal-spatial architecture,…

Scalable and efficient numerical simulations continue to gain importance, as computation is firmly established as the third pillar of discovery, alongside theory and experiment. Meanwhile, the performance of computing hardware grows through…

For reasons of both performance and energy efficiency, high-performance computing (HPC) hardware is becoming increasingly heterogeneous. The OpenCL framework supports portable programming across a wide range of computing devices and is…