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2212 Results

  • Code Generation Guidelines

    In this session, you will be given an overview of the flow used to generate a working simulation using the UVMF code generator.

  • Code Generation Guidelines

  • Machine-Learning-Assisted Agile VLSI Design for Machine Learning

    We will highlight two design automation research directions being pursued in the ASIC and VLSI Research group at NVIDIA: (1) An automated C++-to-layout VLSI flow that leverages HLS tools and open-source HLS-compatible C++ libraries for design productivity; and (2) Machine-learning assisted VLSI design techniques. We will also describe our experience using these tools as part of an agile hardware design flow to build for a deep neural network (DNN) inference accelerator testchip.

  • Assuring the Integrity of RISC-V Cores and SoCs

    The open RISC-V processor architecture is shaking up the intellectual property (IP) and system-on-chip (SoC) worlds. There is great interest and much industry activity underway. However, successful RISC-V core providers will have to verify all aspects of integrity for their designs: functional correctness, safety, security, and trust. SoC developers evaluating potential RISC-V need to check that their standards for design integrity are fully satisfied.

  • A New Approach to Low Power Verification - Power Aware Apps

    This paper demonstrates how Power Aware Apps can help in reporting, debugging and self-checking low power designs. We will also highlight how these apps will help offer an efficient way to significantly save verification effort and time.

  • A New Approach to Low Power Verification: Power Aware Apps

    The effective verification of low power designs has been a challenge for many years now. The IEEE Std 1801-2015 Unified Power Format (UPF) standard for modeling low power objects and concepts is continuously evolving to address the low power challenges of today’s complex designs.

  • Coverage Driven Verification of NVMe Using Questa VIP

  • Using HLS to Accelerate Computer Vision for Autonomous Drive

  • Source Code Download: Fun with UVM Sequences - Coding and Debugging

  • Unraveling the Complexities of Functional Coverage - An Advanced Guide to Simplify Use Models

    In this paper we will outline a set of guidelines for writing an unambiguous coverage model.

  • Results Checking Strategies with Portable Stimulus

    The key to results checking in Portable Stimulus is to understand that different levels of verification and validation environments have different needs when it comes to results checking. In a block-level environment, we might want detailed scoreboarding in addition to an overall per-operation pass/fail. In an SoC environment, we may only need an overall per-operation pass/fail.

  • Transaction Recording: Anywhere Anytime

    This paper will demonstrate a complete transaction recording system for both a stand-alone implementation and a UVM based implementation

  • Transaction Recording: Anywhere Anytime

    Transaction debug can provide visibility where there previously was none. Even in the creation of the examples for this paper, transactions provided several “ah-ha” moments which explained the bug in the example code. It makes debug much faster, requiring only a small amount of work to implement. This paper will demonstrate a complete transaction recording system for both a stand-alone implementation and a UVM based implementation.

  • Portable Stimulus: Is It Revolution or Evolution?

    Many claim the new Portable Test and Stimulus Standard. (PSS) from Accellera will ignite the next revolution in SoC and Electronic System functional verification. Revolutionary innovation seeks to adapt the world to new and better ideas; yet it can be disruptive, expensive and produce unpredicted outcomes.

  • Portable Stimulus: Is It Revolution or Evolution?

    In this session, you will learn how Reuse can be the Evolution that enables the PSS Revolution.

  • An Emulation Strategy for AI and ML Designs

    The ASICs for machine learning applications whether targeted for training or inference will have their own unique characteristics but will nevertheless present quite common and extreme verification challenges that we will present in this session.

  • An Emulation Strategy for AI and ML Designs

    The emergence of Artificial Intelligence is the “next big thing” in the overall The ASICs for machine learning applications whether targeted for training or inference will have their own unique characteristics but will nevertheless present quite common and extreme verification challenges.

  • Tessent: DFT Enablement for AI Devices

    Artificial Intelligence (AI) and other leading edge technologies are experiencing explosive growth in both the number of SoC designs as well as increased complexity. AI processors have architectural features and physical design practices that challenge all aspects of design including DFT. We will investigate some of the DFT challenges faced by AI designs and look at approaches that are currently being used. A few published methodologies and results will be reviewed.

  • Tessent: DFT Enablement for AI Devices

    In this session, we'll learn about some of the DFT challenges faced by AI designs and look at approaches that are currently being used. A few published methodologies and results will be reviewed

  • Deep Learning Accelerator Using HLS

  • Streamlining Plan & Requirements Driven Verification

  • Improving Verification Throughput of Today’s Complex Mixed-Signal ICs

  • Selecting the Most Productive SoC Design Verification Techniques

  • Veloce HYCON - OS-aware IP Development Solution

  • RISC-V Core and SoC: Compliance, Verification, Customization