对CNN FPGA加速器的技术 (例如循环平铺和转换) 优化,同时进行了定量分析计算吞吐量和片内外I/0带宽和建模 通过roof-line模型搜索加速器硬件参数设计空间中最优的方案, 最后通过此建模方案设计了一个加速器,获得当时最优性能密度的CNN加速器。 背景与动机 回答Paper 背景和解决什么问题? 背景 卷积神经网络 (CNN) ...
Source:Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural NetworksAbstract:尽管目前FPGA加速器已经展示出相比通用加速器更好的性能,但其设计空间未能完全发掘。一个重要问题是计算吞吐…
Especially, various accelerators for deep CNN have been proposed based on FPGA platform because it has advantages of high performance, reconfigurability, and fast development round, etc. Although current FPGA accelerators have demonstrated better performance over generic processors, ...
Especially, various accelerators for deep CNN have been proposed based on FPGA platform because it has advantages of high performance, reconfigurability, and fast development round, etc. Although current FPGA accelerators have demonstrated better performance over generic processors, the accele...
In this paper, we first propose a novel FPGA-based CNN accelerator. An accurate performance model of the proposed hardware design is also introduced. To improve accuracy as well as hardware performance, we then apply DNAS and encapsulate the proposed performance model into the objective function....
POM is an end-to-end optimizing framework on MLIR for efficient FPGA-based accelerator generation. POM has the following technical contributions:Programmability: POM provides a decoupled DSL that enables concise descriptions of functions, loops, and arrays. A rich collection of scheduling primitives is...
Optimizing OpenCL-Based CNN Design on FPGA with Comprehensive Design Space Exploration and Collaborative Performance Modeling 文章的目的是:对于给定的CNN模型,通过作者自己设计的框架对设计空间进行探索,找到一个高效的FPGA设计。这个框架包含三部分:LoopTree:在不写源代码的情况下,捕获CNN在FPGA上的硬件结构设计细节...
2.3.3. Automated Accelerator Generation Frameworks Automated accelerator generation frameworks have significantly reduced the complexity and time required to develop efficient DNN accelerators. DNNWeaver [26] automates the generation of FPGA-based accelerators from high-level DNN models by utilizing hand-opt...
•构建了一个端到端的编译和优化堆栈,在高级框架(包括TensorFlow,MXNet,PyTorch,Keras,CNTK)中,多种硬件后端(包括CPU,服务器GPU,移动GPU和基于FPGA的加速算子)特定的工作负荷,部署深度学习。 开源TVM在几家大公司内部量产使用。在服务器级GPU,嵌入式GPU,嵌入式CPU和一个定制的基于FPGA的通用加速器上,使用真实的工...
The SHAKE256 hash generator is integrated into the FPGA design and operates as part of the SIDH accelerator, which executes the encapsulation and decapsulation steps. This integration of SHAKE256 into the FPGA design ensures that the entire cryptographic process can be performed efficiently in hardware...