Farzad Farshchi

I am a PhD student at the University of Kansas advised by Heechul Yun. My research focuses on time predictability in embedded real-time systems with an emphasis on memory interference.

I received my master's degree at the University of Tehran in 2013. There, I worked on approximate arithmetic units for low-power digital signal processing.

Email  |  Google Scholar  |  LinkedIn

Publications
BRU: Bandwidth Regulation Unit for Real-Time Multicore Processors
Farzad Farshchi, Qijing Huang, Heechul Yun
Real-Time and Embedded Technology and Applications Symposium (RTAS), 2020

BRU-FireSim repo

In this paper, we present Bandwidth Regulation Unit (BRU), a drop-in hardware module that enables per-core memory bandwidth regulation at fine-grained time intervals. Additionally, BRU has the ability to regulate the memory access bandwidth of multiple cores collectively to improve the bandwidth utilization.

SpectreGuard: An Efficient Data-centric Defense Mechanism against Spectre Attacks
Jacob Michael Fustos, Farzad Farshchi, Heechul Yun
Design Automation Conference (DAC), 2019

slides | repo

In this paper, we present SpectreGuard, a novel defense mechanism against Spectre attacks. In our approach, sensitive memory blocks (e.g., secret keys) are marked using simple OS/library API, which are then selectively protected by hardware from Spectre attacks via low-cost micro-architecture extension.

Integrating NVIDIA Deep Learning Accelerator (NVDLA) with RISC-V SoC on FireSim
Farzad Farshchi, Qijing Huang, Heechul Yun
Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2), 2019

slides | arXiv | FireSim-NVDLA repo

In this work, we integrate NVDLA into the RISC-V-based Rocket Chip SoC and, with the help of FireSim, we create an FPGA-accelerated cycle-exact simulator which runs on the Amazon EC2 cloud resources. We run YOLOv3 object-detection algorithm on our platfrom for performance evaluation.

Deterministic Memory Abstraction and Supporting Multicore System Architecture
Farzad Farshchi, Prathap Kumar Valsan, Renato Mancuso, Heechul Yun
Euromicro Conference on Real-Time Systems (ECRTS), 2018

slides | arXiv | repo (gem5 and Linux kernel)

In this paper, we make a case that a fundamental problem that prevents efficient and predictable real-time computing on multicore is the lack of a proper memory abstraction to express memory criticality. We, therefore, propose a new holistic resource management approach driven by a new memory abstraction, which we call Deterministic Memory.

Taming Non-Blocking Caches to Improve Isolation in Multicore Real-Time Systems (Best Paper Award)
Prathap Kumar Valsan, Heechul Yun, Farzad Farshchi
Real-Time and Embedded Technology and Applications Symposium (RTAS), 2016

Extended journal version: Addressing Isolation Challenges of Non-Blocking Caches for Multicore Real-Time Systems. Real-time Systems Journal, 2017.

slides | IsolBench benchmark repo

In this paper, we show that cache partitioning does not necessarily ensure predictable cache performance in modern COTS multicore platforms that use non-blocking caches to exploit memory-level-parallelism (MLP).

New Approximate Multiplier for Low-Power Digital Signal Processing
Farzad Farshchi, Muhammad Saeed Abrishami, Sied Mehdi Fakhraie
Computer Architecture and Digital Systems (CADS), 2013

repo (synthesizable Verilog and Matlab model)

In this paper, we propose a new approximate multiplier which utilizes the Broken-Array Multiplier approximation method on the modified Booth multiplier. Our multiplier reduces the total power consumption up to 58% at the cost of a small decrease in output accuracy.

Other Useful Repositories

SiFive's Freedom RISC-V SoC ported to VCU118 FPGA board
I later merged this to the upstream repository when I was interning at SiFive.

Gem5 L2 cache partitioning


website template is cloned from this repository