maculated
发表于 2025-3-30 09:35:01
http://reply.papertrans.cn/17/1601/160094/160094_51.png
反复拉紧
发表于 2025-3-30 12:31:33
Makarand M. Ghangrekar,Bikash R. Tiwariration as well as run-time reconfiguration of applications and their mapping require detailed introspection of the dynamic effects on the target platform. Additionally, extra-functional properties like power consumption and performance characteristics are important metrics to assess the quality of a
Minutes
发表于 2025-3-30 17:19:34
Nishant K. Srivastava,R. C. Tripathin space exploration for dynamically reconfigurable systems. Besides, a middleware to extend the capability of TLM introducing a semantic to interconnect components described at different abstraction levels or languages is added. This middleware allows to automate the creation of the corresponding co
incision
发表于 2025-3-30 21:23:51
Makarand M. Ghangrekar,Bikash R. Tiwari run-time dynamic hardware multithreading. The architecture uses on-chip networking to interconnect routers and computational elements providing a flexible and highly configurable structure. Quadratic routers are reducing total router count while ensuring short communication paths and minimal resour
Bronchial-Tubes
发表于 2025-3-31 03:12:44
http://reply.papertrans.cn/17/1601/160094/160094_55.png
encyclopedia
发表于 2025-3-31 06:56:01
ArchHDL: A Novel Hardware RTL Design Environment in C++ing based on C++. The key features of this language are that (1) designers describe a combinational circuit as a function and (2) the ArchHDL library implements non-blocking assignment in C++. Using these features, designers are able to write a hardware in a Verilog HDL-like style. The source code o
易于
发表于 2025-3-31 10:40:32
http://reply.papertrans.cn/17/1601/160094/160094_57.png
圆木可阻碍
发表于 2025-3-31 15:43:54
Dynamic Memory Management in Vivado-HLS for Scalable Many-Accelerator Architecturesramework with the industrial strength Vivado-HLS tool, and we evaluate its effectiveness with a set of key accelerators from emerging application domains. DMM-HLS delivers significant increase in FPGA’s accelerators density (3.8. more accelerators) in exchange for affordable overheads in terms of de