Paper

Research

RedMule: A Mixed-Precision Matrix-Matrix Operation Engine for Flexible and Energy-Efficient On-Chip Linear Algebra and TinyML Training Acceleration (Full Report)

By Admin 10 Jan 2023 • 4 min read •

Research

RedMule: A Mixed-Precision Matrix-Matrix Operation Engine for Flexible and Energy-Efficient On-Chip Linear Algebra and TinyML Training Acceleration

Abstract RedMulE is a specialized, mixed-precision matrix multiplication engine designed to enable energy-efficient TinyML training, which traditionally requires costly floating-point operations. Integrated into a RISC-V PULP cluster, the engine supports FP16 and hybrid

By Admin 10 Jan 2023 • 2 min read •

Research

TinyVers: A Tiny Versatile System-on-chip with State-Retentive eMRAM for ML Inference at the Extreme Edge (Full Report)

By Admin 9 Jan 2023 • 3 min read •

Research

TinyVers: A Tiny Versatile System-on-chip with State-Retentive eMRAM for ML Inference at the Extreme Edge

Abstract TinyVers is an ultra-low power, versatile System-on-Chip designed for Machine Learning inference at the Extreme Edge, integrating a RISC-V host processor and a dataflow reconfigurable ML accelerator. The SoC leverages state-retentive embedded

By Admin 9 Jan 2023 • 2 min read •

Research

BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU (Full Report)

By Admin 31 Dec 2022 • 3 min read •

Research

BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPU

Abstract BARVINN is an open-source DNN accelerator that enables deep learning inference at arbitrary precision using dedicated, bit-level configurable Processing Elements (PEs). The system is efficiently managed by a dedicated RISC-V CPU controller,

By Admin 31 Dec 2022 • 2 min read •

Research

Generic Tagging for RISC-V Binaries (Full Report)

By Admin 11 Dec 2022 • 3 min read •

Research

Generic Tagging for RISC-V Binaries

Abstract The paper introduces COGENT, a generic instruction tag generator designed for RISC-V binaries to simplify the implementation of custom hardware security solutions without requiring specialized compilers. COGENT associates configurable tags (1 to

By Admin 11 Dec 2022 • 2 min read •

Research

TCN-CUTIE: A 1036 TOp/s/W, 2.72 uJ/Inference, 12.2 mW All-Digital Ternary Accelerator in 22 nm FDX Technology (Full Report)

By Admin 1 Dec 2022 • 3 min read •

Research

TCN-CUTIE: A 1036 TOp/s/W, 2.72 uJ/Inference, 12.2 mW All-Digital Ternary Accelerator in 22 nm FDX Technology

Abstract TCN-CUTIE is a novel, all-digital ternary neural network accelerator implemented in 22 nm FDX technology and integrated into a RISC-V SoC, designed specifically for stringent TinyML constraints. It achieves a record peak

By Admin 1 Dec 2022 • 2 min read •

Research

HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC (Full Report)

By Admin 27 Nov 2022 • 3 min read •

Research

HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC

Abstract HULK-V is an open-source, ultra-low-power, heterogeneous RISC-V System-on-Chip designed to bring full Linux capability and agility to energy-constrained IoT applications. It combines a 64-bit RISC-V processor with an 8-core Programmable Multi-Core Accelerator

By Admin 27 Nov 2022 • 2 min read •