Release Notes

23.0.0

This is an alpha release for the newly supported Alveo V80 which is not intended for production use. Performance on the V80 is not yet optimized.

  • Add support for Alveo V80
  • Add support for vfio-pci; use load-kernel-driver.sh vfio to load it, required for V80
  • Add lock to Vollo RT to prevent concurrent usage of the accelerator
  • Add support for broadcasting non-constant tensors except along the data dimension
  • Add grouped convolution support to vollo_torch.nn.PaddedConv1d
  • Add support for reshape operations
  • Improve VM cycle count estimates for Agilex devices
  • Changes to the API of vollo_torch.nn.Scan: the step function now returns an output tensor and a separate state tensor instead of a single tensor; the forward method now takes both an input_axis and an output_axis instead of a single axis argument

22.1.0

  • Update compatibility with newer IA420F boards (IA420F-0015)

22.0.1

  • Allow weights to be shared in multi-model programs

22.0.0

  • Add support for compiling models with multiple input tensors and multiple output tensors
  • Improve accuracy of LSTM unit
  • Change behavior of VOLLO_FP32_ROUND in Vollo RT so that it's enabled by default; set to 0 to truncate f32 inputs
  • Change vollo-tool reset --pci to vollo-tool reset-pci
  • Expand supported PyTorch stacking and concatenating operations: concatenate, stack, vstack, hstack, row_stack, column_stack, dstack
  • Expand supported PyTorch transposition operations: permute, swapdims, swapaxes, t, T, mT

21.1.1

  • Initial support for torch.nn.LSTM
  • Performance improvements in VM simulation, especially for LSTMs
  • Improve error messages from vollo_torch.fx.nnir.to_nnir for unsupported field accesses (getattr) in PyTorch model
  • Add f32_round argument to vollo_compiler.VM.run methods to choose whether to round or truncate f32 inputs (previously always rounded)
  • Fix handling of non-contiguous input arrays/tensors in Vollo RT Python bindings
  • Fix bug in streaming_transform for tensor sum reductions

21.1.0

  • Support tanh

21.0.0

  • Runtime/bitstream optimisation for small inputs (using MMIO instead of DMA)
  • Scheduling and architecture optimisations
  • Add reset subcommand to vollo-tool
  • Support ReLU via torch.relu

20.0.3

  • Separate bitstreams from Vollo SDK
  • Add c2b64d hw config to support models up to 8M parameters (bitstream and compiler)
  • Improve compiler error messages
  • Fix example build

20.0.2

  • Fix for incorrect vollo_rt_accelerator_num_cores introduced in 20.0.1

20.0.1

  • vollo_rt_add_vm to test the vollo-rt API without an accelerator
  • vollo_rt_load_program_from_buffer and vollo_compiler.Program.{save,load}_bytes
  • Add vollo_torch.nn.RecurrentStateLSTM for modelling streaming LSTM models across forward passes
  • Codegen fix for vollo_torch.nn.Scan
  • Fix incorrect input validation for torch.sum layers
  • Change vollo-rt example to compile with older C compilers

20.0.0

  • Add support for LayerNorm
  • Add support for RMSNorm
  • Add support for sqrt operations (torch.sqrt and torch.rsqrt)
  • Add support for summing over the data dimension
  • Add cycle_count_per_inference and compute_duration_per_inference_us Program methods
  • Add support for a wider range of torch arithmetic operation aliases

19.2.3

  • Downgrade glibc dependency to support systems with glibc >=2.17

19.2.2

  • Add support for torch.div, torch.Tensor.div
  • Fix compiler code generation bug for division

19.2.1

  • Add support for scalars on the left of division
  • Add support for Reciprocal node in ONNX frontend

19.2.0

  • Add support for division by non-constant tensors
  • Fix slicing in ONNX frontend

19.1.1

  • Fix compiler bug in constant folding

19.1.0

  • Add support for partial updates of input data on the accelerator
  • VM simulates Vollo accelerator bit-accurately: bf16_precision argument renamed to bit_accurate and enabled by default
  • vollo-tool includes license self-service
  • Performance improvements due to DMA optimization

18.0.2

  • Add optimize_transforms option to the compiler to improve program schedule in some cases

18.0.1

  • Add fallback to Vollo RT and vollo-tool for when AVX is not available

18.0.0

  • Vollo RT support for using raw DMA buffers to skip IO copy
  • Vollo RT remove redundant/noisy warnings on error: it is the user's responsibility to check returned errors
  • Compiler optimization for Where nodes
  • Compiler scheduling optimizations
  • Vollo IP Core public documentation

0.17.1

  • Fix vollo-tool compatibility with older bitstreams

0.17.0

  • New DMA engine that reduces IO latencies by ~1.3us
  • Initial support for non-streaming LSTM

0.16.0

  • Vollo IP Core now available on request
  • Add C library for configuring IP Core: vollo-cfg
  • Support for slicing/concatenation in the middle of models
  • Support for BatchNorm nodes
  • Support for Scan/LSTMCell nodes
  • Add --io-only option to vollo-onnx
  • Add program-metadata command to vollo-tool
  • Fix compiler bug with transposing streaming dimension
  • Fix accelerator bug in initial state of streaming models

0.15.0

  • Accelerator bug fix

0.14.0

  • Support for filtering dropout layers
  • Instruction packing improvements
  • LSTM performance improvement
  • Improvements to weight sharing

0.13.0

  • Support for multi-model programs
  • Provide Python bindings to Vollo RT: vollo_rt
  • Improved support and error messages for tensor indexing in compiler
  • The unweave transform is now automatic

0.12.2

  • Support for LSTM nodes in ONNX frontend
  • Support for squeezing, unsqueezing, reduce sum, using unweave transformation
  • Improved error reporting in vollo_torch lowering to NNIR

0.12.1

  • vollo-torch fix type hints being incompatible with Python 3.7/3.8
  • vollo-rt.h fix namespacing issue (error_t -> vollo_rt_error_t)
  • Runtime optimisations
  • Added IO only benchmarks

0.12.0

  • Initial support for ONNX models in compiler
  • Support for LSTM nodes
  • Improved error reporting in compiler
  • Compiler API changes
  • New runtime API with access to model metadata
  • HW optimisations (pointwise operations)
  • IA840F support

0.10.1

  • Support for scalar (int, float) literals in pointwise operations in vollo-torch.

0.10.0

  • Architectural changes in bitstream to support compiler
  • Reduced latency from reduced core to core communication in the bitstream
  • Add general model compiler and VM simulation with Python bindings in vollo-python
  • Add PyTorch frontend to model compiler in vollo-torch