6 citations · 9 across the 10 of their papers we have counts for
10 papers
LAAFD: LLM-based Agents for Accelerated FPGA Design
Maxim Moraru, Kamalavasan Kamalakkannan, Jered Dominguez-Trujillo +6
FPGAs offer high performance, low latency, and energy efficiency for accelerated computing, yet adoption in scientific and edge settings is limited by the specialized hardware expe…
Static Estimation of Reuse Profiles for Arrays in Nested Loops
Abdur Razzak, Atanu Barai, Nandakishore Santhi +1
Efficient memory access patterns play a crucial role in determining the overall performance of applications by exploiting temporal and spatial locality, thus maximizing cache local…
Bridging Simulation and Silicon: A Study of RISC-V Hardware and FireSim Simulation
Atanu Barai, Kamalavasan Kamalakkannan, Patrick Diehl +6
RISC-V ISA-based processors have recently emerged as both powerful and energy-efficient computing platforms. The release of the MILK-V Pioneer marked a significant milestone as the…
Scalable, Symbiotic, AI and Non-AI Agent Based Parallel Discrete Event Simulations
Atanu Barai, Stephan Eidenbenz, Nandakishore Santhi
To fully leverage the potential of artificial intelligence (AI) systems in a trustworthy manner, it is desirable to couple multiple AI and non-AI systems together seamlessly for co…
Static Reuse Profile Estimation for Array Applications
Abdur Razzak, Atanu Barai, Nandakishore Santhi +1
Reuse distance analysis is a widely recognized method for application characterization that illustrates cache locality. Although there are various techniques to calculate the reuse…
LLVM Static Analysis for Program Characterization and Memory Reuse Profile Estimation
Atanu Barai, Nandakishore Santhi, Abdur Razzak +2
Profiling various application characteristics, including the number of different arithmetic operations performed, memory footprint, etc., dynamically is time- and space-consuming.…
BB-ML: Basic Block Performance Prediction using Machine Learning Techniques
Hamdy Abdelkhalik, Shamminuj Aktar, Yehia Arafa +8
Recent years have seen the adoption of Machine Learning (ML) techniques to predict the performance of large-scale applications, mostly at a coarse level. In contrast, we propose to…
PPT-Multicore: Performance Prediction of OpenMP applications using Reuse Profiles and Analytical Modeling
Atanu Barai, Yehia Arafa, Abdel-Hameed Badawy +3
We present PPT-Multicore, an analytical model embedded in the Performance Prediction Toolkit (PPT) to predict parallel application performance running on a multicore processor. PPT…
PPT-SASMM: Scalable Analytical Shared Memory Model: Predicting the Performance of Multicore Caches from a Single-Threaded Execution Trace
Atanu Barai, Gopinath Chennupati, Nandakishore Santhi +3
Performance modeling of parallel applications on multicore processors remains a challenge in computational co-design due to multicore processors' complex design. Multicores include…
Modeling Shared Cache Performance of OpenMP Programs using Reuse Distance
Atanu Barai, Gopinath Chennupati, Nandakishore Santhi +2
Performance modeling of parallel applications on multicore computers remains a challenge in computational co-design due to the complex design of multicore processors including priv…