Profiling your Applications using the Linux Perf ToolsemBO_Conference
This document provides an overview of using the Linux perf tools to profile applications. It discusses setting up perf, benchmarking applications, profiling both CPU usage and sleep times, and analyzing profiling data. The document covers perf commands like perf record to collect profiling data, perf report to analyze the data, and perf script to convert it to other formats. It also discusses profiling options like call graphs and collecting kernel vs. user mode events.
BPF of Berkeley Packet Filter mechanism was first introduced in linux in 1997 in version 2.1.75. It has seen a number of extensions of the years. Recently in versions 3.15 - 3.19 it received a major overhaul which drastically expanded it's applicability. This talk will cover how the instruction set looks today and why. It's architecture, capabilities, interface, just-in-time compilers. We will also talk about how it's being used in different areas of the kernel like tracing and networking and future plans.
This document discusses NNgen, a tool for generating hardware implementations of neural networks from high-level models. It can generate optimized RTL and IP-XACT from models defined using frameworks like TensorFlow or ONNX. NNgen uses the Veriloggen library for hardware synthesis from Python, generating FSMs and scheduled pipelines to implement DNN layers as hardware accelerators. It aims to bridge the gap between deep learning and hardware for deploying neural networks in embedded systems.
Profiling your Applications using the Linux Perf ToolsemBO_Conference
This document provides an overview of using the Linux perf tools to profile applications. It discusses setting up perf, benchmarking applications, profiling both CPU usage and sleep times, and analyzing profiling data. The document covers perf commands like perf record to collect profiling data, perf report to analyze the data, and perf script to convert it to other formats. It also discusses profiling options like call graphs and collecting kernel vs. user mode events.
BPF of Berkeley Packet Filter mechanism was first introduced in linux in 1997 in version 2.1.75. It has seen a number of extensions of the years. Recently in versions 3.15 - 3.19 it received a major overhaul which drastically expanded it's applicability. This talk will cover how the instruction set looks today and why. It's architecture, capabilities, interface, just-in-time compilers. We will also talk about how it's being used in different areas of the kernel like tracing and networking and future plans.
This document discusses NNgen, a tool for generating hardware implementations of neural networks from high-level models. It can generate optimized RTL and IP-XACT from models defined using frameworks like TensorFlow or ONNX. NNgen uses the Veriloggen library for hardware synthesis from Python, generating FSMs and scheduled pipelines to implement DNN layers as hardware accelerators. It aims to bridge the gap between deep learning and hardware for deploying neural networks in embedded systems.