RISC-V userspace emulator library
libriscv is a RISC-V userspace emulator that is highly embeddable and configurable. This project is intended to be included in a CMake build system, and should not be installed anywhere. There are several CMake options that control RISC-V extensions and how the emulator behaves.
Userspace emulation means running ELF programs in a sandbox, trapping and emulating system calls. There is built-in support for Linux userspace emulation, however anyone can implement userspace support for other OSes, and even ELF loading is optional.
Instruction counting is used to limit the time spent executing code and can be used to prevent infinite loops. It can also help keep frame budgets for long running background scripting tasks as running out of instructions simply halts execution, and it can be resumed from where it stopped.
While this emulator has a focus on performance, one higher priority is the ability to map any memory anywhere with permissions, custom fault handlers and such things. This allows you to take the memory of one machine and map it into another with copy-on-write mechanisms, and does have a slight performance penalty compared to an emulator that can only have sequential memory.
Benchmarks
One motivation when writing this emulator was to use it in a game engine, and so it felt natural to compare against Lua, which I was already using. Lua is excellent and easy to embed, and does not require ahead-of-time compilation. However, compiled code should in theory be faster.
Installing a RISC-V GCC compiler
On Ubuntu and Linux distributions like it, you can install a 64-bit RISC-V GCC compiler for running Linux programs with a one-liner:
sudo apt install gcc-11-riscv64-linux-gnu g++-11-riscv64-linux-gnu
Depending on your distro you may have access to GCC versions 10, 11 and 12. Now you have a full Linux C/C++ compiler for RISC-V. It is typically configured to use the C-extension, so make sure you have that enabled.
To build smaller and leaner programs you will need a (limited) Linux userspace environment. You sometimes need to build this cross-compiler yourself:
git clone https://github.com/riscv/riscv-gnu-toolchain.git
cd riscv-gnu-toolchain
./configure --prefix=$HOME/riscv --with-arch=rv32g --with-abi=ilp32d
make
This will build a newlib cross-compiler with C++ exception support. The ABI is ilp32d, which is for 32-bit and 64-bit floating-point instruction set support. It is much faster than software implementations of binary IEEE floating-point arithmetic.
Note that if you want a full glibc cross-compiler instead, simply appending linux to the make command will suffice, like so: make linux. Glibc produces larger binaries but has more features, like sockets and threads.
git clone https://github.com/riscv/riscv-gnu-toolchain.git
cd riscv-gnu-toolchain
./configure --prefix=$HOME/riscv --with-arch=rv64g --with-abi=lp64d
make
The incantation for 64-bit RISC-V. Not enabling the C-extension for compressed instructions results in faster emulation.
The last step is to add your compiler to PATH so that it becomes visible to build systems. So, add this at the bottom of your .bashrc file in the home (~) directory:
export PATH=$PATH:$HOME/riscv/bin
Building and running a test program
From one of the binary subfolders:
$ ./build.sh
Which will produce a RISC-V binary in the sub-projects build folder, depending on the example. Some examples require you to install a compiler for that programming language.
Building the emulator and booting the newlib hello_world:
cd emulator
./build.sh
./rvlinux ../binaries/linux64/build/hello_worldThe emulator is built 3 times for different purposes. rvmicro is built for micro-environments with custom heap and threads. rvnewlib has hooked up enough system calls to run newlib programs. rvlinux has all the system calls necessary to run a normal userspace linux program. Each emulator is capable of running both 32- and 64-bit RISC-V programs.
Example programs
Building and running your own ELF files that can run in freestanding RV32G is quite challenging, so consult the barebones example! It's a bit like booting on bare metal, except you can more easily implement system functions. The fun part is of course the extremely small binaries and total control over the environment.
The newlib example projects have much more C and C++ support, but still misses things like environment variables and such. This is a deliberate design as newlib is intended for embedded development. It supports C++ RTTI and exceptions, and is the best middle-ground for running a fuller C++ environment that still produces small binaries.
The linux example projects use the Linux-configured cross compiler and will expect you to implement quite a few system calls just to get into int main(). In addition, you will have to setup argv, env and the aux-vector. There are helper methods to do all of this, and you should have a look at the emulator on how to set it up.
Finally, the micro project implements the absolutely minimal freestanding RV32GC C/C++ environment. You won't have a heap implementation, so no new/delete. And you can't printf values because you don't have a C standard library, so you can only write strings and buffers using the write system call. Still, the stripped binary is only 784 bytes, and will execute only ~120 instructions running the whole program! The micro project actually initializes zero-initialized memory, calls global constructors and passes program arguments to main.
Building for Windows
There is a build_mingw.sh script that can build the emulator for MinGW 64 when cross-compiling on Linux. To be able to build it, install the g++-mingw-w64-x86-64 package. If you are building inside MinGW 64 on (actual) Windows, then you should not have to do anything special. You will need the common build tools like make, cmake and a C++17-capable compiler.
Remote debugging using GDB
If you have built the emulator, you can use GDB=1 ./rvlinux /path/to/program to enable GDB to connect. Most distros have gdb-multiarch, which is a separate program from the default gdb. It will have RISC-V support already built in. Start your GDB like so: gdb-multiarch /path/to/program. Make sure your program is built with -O0 and with debuginfo present. Then, once in GDB connect with target remote localhost:2159. Now you can step through the code.
Most modern languages embed their own pretty printers for debuginfo which enables you to go line by line in your favorite language.
Instruction set support
The emulator currently supports RV32GC, RV64GC (IMAFDC) and RV128G. The F and D-extensions should be 100% supported (32- and 64-bit floating point instructions). Atomics support is present and has been tested with multiprocessing, but there is no extensive test suite. The Golang runtime uses atomics extensively.
The 128-bit ISA support is experimental, and the specification is not yet complete. There is neither toolchain support, nor is there an ELF format for 128-bit machines. There is an emulator that specifically runs a custom crafted 128-bit program in the emu128 folder.
Note: There is no support for the E- and Q-extensions. Zba is supported. A minimal set of the V-extension is currently being worked on. Binary translation currently only supports RV32G and RV64G. The fastest arch combo is rv64gv_zba right now.
Example usage when embedded into a project
Load a Linux program built for RISC-V and run through main:
#include <libriscv/machine.hpp>
int main(int /*argc*/, const char** /*argv*/)
{
// Load ELF binary from file
const std::vector<uint8_t> binary /* = ... */;
using namespace riscv;
// Create a 64-bit machine (with default options, see: libriscv/common.hpp)
Machine<RISCV64> machine { binary };
// Add program arguments on the stack, and set a few basic
// environment variables.
machine.setup_linux(
{"myprogram", "1st argument!", "2nd argument!"},
{"LC_TYPE=C", "LC_ALL=C", "USER=root"});
// Add all the basic Linux system calls.
// This includes `exit` and `exit_group` which we will override below.
machine.setup_linux_syscalls();
// Install our own `exit` system call handler (for all 64-bit machines).
Machine<RISCV64>::install_syscall_handler(93, // exit
[] (Machine<RISCV64>& machine) {
const int code = machine.return_value <int> ();
printf(">>> Program exited, exit code = %d\n", code);
machine.stop();
});
// We also use the same system call handler again for `exit_group`,
// which is another way that C libraries will use to end the process.
Machine<RISCV64>::install_syscall_handler(94, // exit_group
Machine<RISCV64>::syscall_handlers.at(93));
// NOTE: We absolutely don't have to create our own system calls handlers,
// but it's fun to take control of the environment inside the machine!
// This function will run until the exit syscall has stopped the
// machine, an exception happens which stops execution, or the
// instruction counter reaches the given 1M instruction limit:
try {
machine.simulate(1'000'000UL);
} catch (const std::exception& e) {
fprintf(stderr, ">>> Runtime exception: %s\n", e.what());
}
}In order to have the machine not throw an exception when the instruction limit is reached, you can call simulate with the template argument false, instead:
machine.simulate<false>(1'000'000UL);If the machine runs out of instructions, it will simply stop running. Use machine.instruction_limit_reached() to check if the machine stopped running because it hit the instruction limit.
You can limit the amount of (virtual) memory the machine can use like so:
const uint32_t memsize = 1024 * 1024 * 64u;
riscv::Machine<riscv::RISCV32> machine { binary, { .memory_max = memsize } };You can limit the amount of instructions to simulate at a time like so:
const uint64_t max_instructions = 2500;
machine.simulate(max_instructions);If the simulator runs out of instructions it will throw an exception. The exception is harmless and is only inteded to inform that the task took too long to complete. It is possible to keep calling simulate() until the machine is finished running. It is finished running when the call to simulate does not throw an exception.
When making a function call into the VM you can also add this limit as a template parameter to the vmcall() function.
You can find details on the Linux system call ABI online as well as in the syscalls.hpp, and syscalls.cpp files in the src folder. You can use these examples to handle system calls in your RISC-V programs. The system calls is emulate normal Linux system calls, and is compatible with a normal Linux RISC-V compiler.
Handling instructions one by one
You can create your own custom instruction loop if you want to do things manually by yourself:
#include <libriscv/machine.hpp>
#include <libriscv/rv32i_instr.hpp>
...
Machine<RISCV64> machine{binary};
machine.setup_linux(
{"myprogram"},
{"LC_TYPE=C", "LC_ALL=C", "USER=root"});
machine.setup_linux_syscalls();
// Instruction limit is used to keep running
machine.set_max_instructions(1'000'000UL);
while (!machine.stopped()) {
auto& cpu = machine.cpu;
// Get 32- or 16-bits instruction
auto instr = cpu.read_next_instruction();
// Print the instruction to terminal
printf("%s\n",
cpu.current_instruction_to_string().c_str());
// Decode instruction to get instruction info
auto decoded = cpu.decode(instr);
// Execute one instruction, and increment PC
decoded.handler(cpu, instr);
cpu.increment_pc(instr.length());
}NOTE: Does not work when RISCV_DECODER_REWRITER is enabled, as it modifies (rewrites) instructions. Alternative is to use the already decoded instructions from the decoder cache and the rest will largely be the same.
Setting up your own machine environment
You can create a 64kb machine without a binary, and no ELF loader will be invoked.
Machine<RISCV32> machine;
machine.setup_minimal_syscalls();
std::vector<uint32_t> my_program {
0x29a00513, // li a0,666
0x05d00893, // li a7,93
0x00000073, // ecall
};
// Set main execute segment (12 instruction bytes)
const uint32_t dst = 0x1000;
machine.cpu.init_execute_area(my_program.data(), dst, 12);
// Jump to the start instruction
machine.cpu.jump(dst);
// Geronimo!
machine.simulate(1'000ul);The fuzzing program does this, so have a look at that.
Documentation
Why a RISC-V library
It's a drop-in sandbox. Perhaps you want someone to be able to execute C/C++ code on a website, safely? It can step through RISC-V programs line by line showing registers and memory locations. It also has some extra features that allow you to make function calls into the guest program. I think it's pretty cool stuff.
What to use for performance
Using Clang for libriscv is a little bit faster on some benchmarks. GCC-12 has for the most part catched up.
Building the fastest possible RISC-V binaries for libriscv is a hard problem, but I am working on that in my rvscript repository. It's a complex topic that cannot be explained in one paragraph.
If you have arenas available you can replace the default page fault handler with your own that allocates faster than regular heap. If you intend to use many (read hundreds, thousands) of machines in parallel, you absolutely must use the Machine forking constructor. It will apply copy-on-write to all pages on the newly created machine and share text, rodata and the instruction cache.
Multiprocessing
There is multiprocessing support, but it is in its early stages. It is achieved by calling a (C/SYSV ABI) function on many machines, with differing CPU IDs. The input data to be processed should exist beforehand. It is not well tested, and potential page table races are not well understood. That said, it passes manual testing and there is a unit test for the basic cases. With multiprocessing I was able to achieve 3x speedup using 4 CPUs for 8192 dot-product calculations.
Binary translation
Instead of JIT, the emulator supports translating binaries to native code using any local C compiler. You can control compilation by passing CC and CFLAGS environment variables to the program that runs the emulator. You can show the compiler arguments using VERBOSE=1. Example: CFLAGS=-O2 VERBOSE=1 ./myemulator.
The binary translation feature (accessible by enabling the RISCV_EXPERIMENTAL CMake option) can greatly improve performance in some cases, but requires compiling the program on the first run. The RISC-V binary is scanned for code blocks that are safe to translate, and then a C compiler is invoked on the generated code. This step takes a long time. The resulting code is then dynamically loaded and ready to use. The feature is a work in progress.
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