| #!/bin/bash | |
| # | |
| # Usage: runperf ./my-benchmark-binary | |
| # | |
| # Script to run a benchmark / performance test in decent conditions. Based on: | |
| # - https://www.llvm.org/docs/Benchmarking.html | |
| # - "Performance Analysis and Tuning on Modern CPU" by Denis Bakhvalov, Appendix A. | |
| # - https://github.com/andikleen/pmu-tools | |
| # | |
| # Note that this doesn't do any actual benchmarking, your binary must be able to do that all by itself. |
In reverse chronological order from gist creation:
A compile-time 4-Bit Virtual Machine implemented in TypeScript's type system. Capable of running a sample 'FizzBuzz' program.
Syntax emits zero JavaScript.
type RESULT = VM<
[
["push", N_1], // 1
["push", False], // 2
["peek", _], // 3
This document was originally written several years ago. At the time I was working as an execution core verification engineer at Arm. The following points are coloured heavily by working in and around the execution cores of various processors. Apply a pinch of salt; points contain varying degrees of opinion.
It is still my opinion that RISC-V could be much better designed; though I will also say that if I was building a 32 or 64-bit CPU today I'd likely implement the architecture to benefit from the existing tooling.
Mostly based upon the RISC-V ISA spec v2.0. Some updates have been made for v2.2
The RISC-V ISA has pursued minimalism to a fault. There is a large emphasis on minimizing instruction count, normalizing encoding, etc. This pursuit of minimalism has resulted in false orthogonalities (such as reusing the same instruction for branches, calls and returns) and a requirement for superfluous instructions which impacts code density both in terms of size and
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
