SimpleSSD is a high-fidelity SSD simulation framework designed for education and research. It builds a complete storage stack from scratch, models all detailed characteristics of SSD internal hardware and software, provides high simulation speed, and can be integrated into publicly available full-system simulators. We have verified our simulation framework with commercial SSDs, and our experiments demonstrate high accuracy of simulation results.

NVMe is widely used by diverse types of storage and non-volatile memory subsystems as a de facto high-speed I/O interface. Industries secure their own intellectual property (IP) for high-speed NVMe controllers and explore software-stack challenges with future fast NVMe storage cards.

GraphTensor is a comprehensive acceleration framework for GNN computation that supports efficient parallel processing on large graphs. GraphTensor offers a set of easy-to-use GNN-specific programming interfaces, enabling its users to implement diverse GNN models. Supporting parallel embedding processing through a vector-centric approach and applying pipeline preprocessing, GraphTensor resolves the performance issues in conventional frameworks such as PyG and DGL.

OpenNVM can cope with diversified memory transactions and cover a variety of evaluation workloads without any FPGA logic block updates. In our design, while evaluation scripts are managed by a host, all the NVM-related transactions are handled by our FPGA-based NVM controller connected to the hardware circuit board that can accommodate different types of NVM products and our custom-made power measurement board. This open scheme has been developed to generate exhaustive, empirical data of emerging non-volatile memory in a configured, programmable FPGA-based hardware prototype in order to support research on memory systems, especially non-volatile memories.

NANDFlashSim is a flash simulation model that is decoupled from specific flash firmware and supports detailed NAND flash transactions with cycle accuracy. This low-level simulation framework can enable research on the NAND flash memory system itself as well as many NAND flash-based devices such as Flash-based SSD, eMMC, CF memory card, mobile NAND flash media. We have evaluated hundreds of thousands of NANDFlashSim instances on NERSC Hopper and Carver supercomputers.

Storage traces are widely used for storage simulation and system evaluation. Since high performance SSD, flash array and NVM systems exhibit different I/O timing behaviors, the traditional traces need to be revised or collected on relatively modern systems. To address this, we are collecting different types of traces with many different combinations of devices and systems. Our trace repository distributes traces collected on Kandemir, Wilson, John and Donofrio machines under different types of parallel file systems such as Lustre and Ceph. We hope to expand the repository with additional traces that help the storage-systems and architecture communities conduct better, reproducible research.

FlashGPU is a MacSim-based GPU simulation model that integrates with SimpleSSD. This research framework can be basically used for exploring an emerging GPU platform that would employ flash within its discrete device. The current version of FlashGPU replaces global memory with Z-NAND that exhibits ultra-low latency. It also architects a flash core to manage request dispatches and address translations underneath L2 cache banks of GPU cores. While Z-NAND is a hundred times faster than conventional 3D-stacked flash, its latency is still longer than DRAM. We expect that diverse persistent-memory subsystems, algorithms, and controllers can be explored to address the long-latency challenges that arise when flash is placed within a large GPU-core network.

SystemC interface converter (SCIC) enables DRAMSim to be integrated with comprehensive pin-level system simulation models. SCIC manages protocol differences between the DRAMSim and SystemC interfaces. SCIC also provides storage resources for modeling data movement. Additionally in this project, a pin-level protocol (Transaction Level 0) is introduced into the DRAMSim memory-system model; therefore, the memory system can be harmonized to other simulators that employ SystemC or HDL simulation.

In this simulation framework, NVRAM software stack on multi-channel architecture are fully implemented, and diverse parameters/algorithms are reconfigurable (e.g., buffer cache, NVMHCIs, flash drivers, flash translation layers, physical layouts). Hardware components are emulated in a cycle-level by multiple NANDFlashSim instances, DRAM simulation instances, and virtual channel and controller modules. Flashwood can also evaluate dynamic energy and power consumption by catching all the different components' activities. The code for the flash software in the framework and device simulation code are around two hundreds thousand of lines and ten thousand of lines, respectively.

CoDEN is a novel hardware/software co-design emulation platform, which not only offers flexible/scalable design space that can employ a broad range of SSD controller and firmware policies, but also capture the details of entire software/hardware stacks for SSD-accelerated near data processing. Our CoDEN can be connected to a host through PCI Express (PCIe) interface, a high performance memory bus, and recognized by the host as a real SSD storage device.

The SSD emulation kernel driver provides a logical volume to native file systems (e.g., Windows NTFS, EXT4) as a pseudo SSD device. Virtual channels and cycle-level NAND flash simulation instances of Asura model the actual runtime in cycle accurate by hooking kernel I/O dispatch routines. To enable large-scale SSD emulation, the driver only stores metadata of kernel modules, data of flash firmware and device simulation models -- omits actual data contents. In addition, Asura can be initiated as multiple driver instances in order to emulate an SSD RAID system. Asura has been implemented by a filter driver (WDM) for Windows (NTFS) and loadable kernel module for Linux (EXT4).