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IBM Analog Hardware Acceleration Kit 0.8.0
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@kaoutar55 kaoutar55 released this 14 Jul 20:20
· 61 commits to master since this release
v0.8.0
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Learn about vigilant mode.

[0.8.0] - 2023/07/14

Added

  • Added new tutorial notebooks to cover the concepts of training,
    hardware-aware training, post-training calibration, and extending aihwkit functionality (#518, #523, #526)
  • Calibration of input ranges for inference (#512)
  • New analog in-memory training algorithms: Chopped Tiki-taka II (#512)
  • New analog in-memory training algorithms: AGAD (#512)
  • New training presets: ReRamArrayOMPresetDevice,
    ReRamArrayHfO2PresetDevice, ChoppedTTv2*, AGAD* (#512)
  • New correlation detection example for comparing specialized analog SGD
    algorithms (#512)
  • Simplified build_rpu_config script for generating RPUConfigs for
    analog in-memory SGD (#512)
  • CustomTile for customization of in-memory training algorithms (#512)
  • Pulse counters for pulsed analog training (#512)
  • TorchInferenceTile for a fully torch-based analog tile for
    inference (not using the C++ RPUCuda engine), supporting a subset of MVM nonidealities (#512)
  • New inference preset StandardHWATrainingPreset (#512)
  • New inference noise model ReRamWan2022NoiseModel (#512)
  • Improved HWA-training for inference featuring input and output range
    learning and more (#512)
  • Improved CUDA memory management (using torch cached GPU memory for
    internal RPUCuda buffer) (#512)
  • New layer generator: analog_layers() loops over layer modules (except
    container) (#512)
  • AnalogWrapper for wrapping a full torch module (Without using
    AnalogSequential) (#512)
  • convert_to_digital utility (# 512)
  • TileModuleArray for logical weight matrices larger than a single tile. (#512)
  • Dumping of all C++ fields for accurate analog training saving and
    training continuation after checkpoint load. (#512)
  • apply_write_noise_on_set for pulsed devices. (#512)
  • Reset device now also for simple devices. (#512)
  • SoftBoundsReference, PowStepReference for explicit reference
    subtraction of symmetry point in Tiki-taka (#512)
  • Analog MVM with output-to-output std-deviation variability
    (output_noise_std) (#512)
  • Plotting utility for weight errors (#512)
  • per_batch_sample weight noise injections for TorchInferenceRPUConfig (#512)

Fixed

  • BERT example 24 using AnalogWrapper (#514)
  • Cuda supported testing in examples based on AIHWKIT compilation (#513)
  • Fixed compilation error for CUDA 12.1. (#500)
  • Realistic read weights could have applied the scales wrongly (#512)

Changed

  • Major re-organization of AnalogTiles for increased modularity
    (TileWithPeriphery, SimulatorTile, SimulatorTileWrapper). Analog
    tile modules (possibly array of analog tiles) are now also torch Module. (#512)
  • Change in tile generators: analog_model.analog_tiles() now loops over
    all available tiles (in all modules) (#512)
  • Import and file position changes. However, user can still import RPUConfig
    related modules from aihwkit.simulator.config (#512)
  • convert_to_analog now also considered mapping. Set
    mapping.max_out_size = 0 and mapping.max_out_size = 0 to avoid this. (#512)
  • Mapped layers now use TileModuleArray array by default. (#512)
  • Checkpoint structure is different than previous
    versions. utils.legacy_load provides a way to load old checkpoints. (#512)

Removed

  • realistic_read_write is removed from some high-level function. Use
    program_weights (after setting the weights) or read_weights
    for realistic reading (using weight estimation technique). (#512)
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