Hands-on Session

In this workshop, we will provide hands-on sessions on the following tools: MUMAX, VAMPIRE, NeuroSIM and DESTINY. More details on these tools are provided below.

1. MUMAX is a GPU-accelerated micromagnetic simulation tool designed for simulating and modeling magnetic systems at the nanoscale. It is widely used in the field of spintronics, magnetic storage devices, and magnetism research. Here are its main uses:

1. Simulating Magnetic Dynamics

• It solves the Landau-Lifshitz-Gilbert (LLG) equation, which describes the dynamics of magnetic moments under the influence of applied fields, thermal effects, and spin torques.

• Useful for studying magnetization processes, domain wall motion, skyrmions, and spin-wave dynamics.

2. Designing Magnetic Devices

• Helps design advanced magnetic devices like spintronic devices, MRAM (Magnetoresistive Random Access Memory), and magnetic sensors by predicting their behavior at the nanoscale.

3. Exploring Magnetization Configurations

·        Simulates how magnetic domains and configurations change due to Applied magnetic fields, Current-driven spin torques, Temperature fluctuations.

2. VAMPIRE software package is a powerful simulation tool used for atomic-scale spin dynamics modeling. It is particularly suited for investigating the magnetic properties and behaviors of materials at the atomic level, especially those where thermal effects and atomistic interactions play a crucial role.

Primary Uses of VAMPIRE

1. Atomistic Spin Dynamics

   • Simulates magnetic systems by solving Landau-Lifshitz-Gilbert (LLG) equations at the atomic level.

   • Incorporates exchange interactions, anisotropies, and Zeeman effects with atomic resolution.

2. Thermal Effects in Magnetism

   • Models temperature-dependent magnetic properties, including:

     • Curie temperature (temperature where a material loses ferromagnetic properties).

     • Phase transitions in magnetic systems.

   • Suitable for understanding magnetization dynamics at finite temperatures.

3. Magnetic Material Design

   • Assists in designing advanced magnetic materials for applications like:

     • Heat-assisted magnetic recording (HAMR)

     • Spintronic devices

   • Explores how material properties (e.g., anisotropy, exchange interaction) affect performance.

3. NeuroSIM is a specialized simulation tool used for the design and evaluation of neuromorphic computing systems, particularly those based on hardware implementations of neural networks. It bridges the gap between the algorithmic-level simulation of neural networks and the circuit/device-level design of neuromorphic hardware.

Primary Uses of NeuroSIM

1. Neuromorphic Hardware Design

   • Models the implementation of neural networks on hardware platforms, including analog, digital, and hybrid systems.

   • Enables the exploration of hardware-friendly neural network architectures.

2. Device-Level and Circuit-Level Simulation

   • Incorporates the physical characteristics of emerging non-volatile memory (NVM) devices, such as:

     • Resistive RAM (RRAM)

     • Phase-Change Memory (PCM)

     • Spin-Transfer Torque Magnetic RAM (STT-MRAM)

   • Simulates the effects of device non-idealities (e.g., noise, variability, endurance) on system performance.

3. System-Level Evaluation

   • Quantifies metrics such as energy consumption, delay, and area (EDA) for neuromorphic systems.

   • Analyzes how hardware limitations affect neural network accuracy, efficiency, and scalability.

4. DESTINY is a tool for modeling 3D (and 2D) cache designs using SRAM, embedded DRAM (eDRAM), spin transfer torque RAM (STT-RAM), resistive RAM (ReRAM) and phase change RAM (PCM). DESTINY is very useful for performing design-space exploration across several dimensions, such as optimizing for a target (e.g. latency, area or energy-delay product) for a given memory technology, choosing the suitable memory technology or fabrication method (i.e. 2D v/s 3D) for a given optimization target.

Primary Uses of DESTINY

1. Architectural modelling of cache/RAM

·        Reports metrics like area, latency, energy, leakage power for data and tag arrays of a cache

·        Allows optimizing for a target (e.g. latency, area or energy-delay product)

·        Allows design-space exploration.