Shuhai is a benchmarking-memory tool that allows FPGA programmers to demystify all the underlying details of memories, e.g., HBM and DDR4, on a Xilinx FPGA
In terms of benchmarking memory, it can be done better on FPGA, rather than on CPU/GPU. When benchmarking memory on an FPGA, the benchmarking hardware engine can directly attach to the memory such that there is no noise between the targeted memory and the benchmarking engine.
With Shuhai, before implementing the concrete application that contains a particular memory access pattern on the FPGA, we are able to benchmark the corresponding memory access pattern to make sure that the memory side will not be the bottleneck.
Links:
📄 https://ieeexplore.ieee.org/document/9114755
💾 https://github.com/RC4ML/Shuhai
#memory #ddr #hbm #benchmark
@fpgasic
In terms of benchmarking memory, it can be done better on FPGA, rather than on CPU/GPU. When benchmarking memory on an FPGA, the benchmarking hardware engine can directly attach to the memory such that there is no noise between the targeted memory and the benchmarking engine.
With Shuhai, before implementing the concrete application that contains a particular memory access pattern on the FPGA, we are able to benchmark the corresponding memory access pattern to make sure that the memory side will not be the bottleneck.
Links:
📄 https://ieeexplore.ieee.org/document/9114755
💾 https://github.com/RC4ML/Shuhai
#memory #ddr #hbm #benchmark
@fpgasic
👍7❤1🔥1
A Large-Scale SPICE Netlist Dataset for Analog Circuits by Harnessing AI
Masala-CHAI is the first fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists.
Automating workflow could accelerate the creation of finetuned LLMs for analog circuit design and verification. We identify key challenges in this automation and evaluate the multi-modal capabilities of state-of-the-art LLMs, particularly GPT-4, to address these issues.
This approach aims to create an end-to-end SPICE netlist generator from circuit schematic images, tackling the long-standing hurdle of accurate netlist generation. Our framework demonstrates significant performance improvements, tested on approximately 2,100 schematics of varying complexity.
Links:
📄 https://arxiv.org/abs/2411.14299
💾 https://github.com/jitendra-bhandari/Masala-CHAI
#LLM #LLM4EDA #analog #SPICE #EDA #simulation
@fpgasic
Masala-CHAI is the first fully automated framework leveraging large language models (LLMs) to generate Simulation Programs with Integrated Circuit Emphasis (SPICE) netlists.
Automating workflow could accelerate the creation of finetuned LLMs for analog circuit design and verification. We identify key challenges in this automation and evaluate the multi-modal capabilities of state-of-the-art LLMs, particularly GPT-4, to address these issues.
This approach aims to create an end-to-end SPICE netlist generator from circuit schematic images, tackling the long-standing hurdle of accurate netlist generation. Our framework demonstrates significant performance improvements, tested on approximately 2,100 schematics of varying complexity.
Links:
📄 https://arxiv.org/abs/2411.14299
💾 https://github.com/jitendra-bhandari/Masala-CHAI
#LLM #LLM4EDA #analog #SPICE #EDA #simulation
@fpgasic
👍5❤3🔥3
Automated SV Assertion Interface Generator:
It generates a SV assertion interface for a given RTL design. It analyzes the RTL code to extract ports and registers, and creates an interface that can be used for writing assertions.
Features
▫️ Automatically detects the top-level module in the design hierarchy
▫️ Extracts ports and registers from the RTL code
▫️ Handles naming conflicts by using hierarchical paths
▫️ Generates a bind statement for easy integration
▫️ Creates well-formatted and organized interface code
▫️ Supports different modes for interface generation (SPY signals source):
◾️ Ports only (input | output | inout)
◾️ Registers only (signals with "_s" suffix)
◾️ Both ports and registers (default)
Links
💾 https://github.com/Inkub/SV-assertions-IF-generator
#SVA #SV #generator #checker
@fpgasic
It generates a SV assertion interface for a given RTL design. It analyzes the RTL code to extract ports and registers, and creates an interface that can be used for writing assertions.
Features
▫️ Automatically detects the top-level module in the design hierarchy
▫️ Extracts ports and registers from the RTL code
▫️ Handles naming conflicts by using hierarchical paths
▫️ Generates a bind statement for easy integration
▫️ Creates well-formatted and organized interface code
▫️ Supports different modes for interface generation (SPY signals source):
◾️ Ports only (input | output | inout)
◾️ Registers only (signals with "_s" suffix)
◾️ Both ports and registers (default)
Links
💾 https://github.com/Inkub/SV-assertions-IF-generator
#SVA #SV #generator #checker
@fpgasic
6👍5❤4🔥4