ShuraCore team uses ready-made JIT and AOT compilers to improve the customer’s product. JIT and AOT are an implantation method that will allow you to reach new heights for your software. As part of this collaboration, we will create a generic JIT or AOT compiler implementation concept to use methodologies applied to improve your product and business solution. Our team is interested in creating a unique and successful JIT or AOT compiler for our customers.
AsmJit is a complete JIT and AOT assembler for the C++ language. It can generate native code for x86 and x64 architectures and supports the entire x86/x64 command set from the legacy MMX to the newest AVX512. It has a type-safe API that allows the C++ compiler to perform compile-time semantic checks even before the compiled code is generated or executed.
A lightweight JIT compiler based on MIR (Average Internal Representation).
Cross-platform JIT engine based on Eclipse OMR.
A small JIT engine was originally written by Adobe for Flash.
The MCJIT class is the JIT implementation for LLVM.
The front-end compiler, analyzing the source code, creates an internal representation of the program – an intermediate representation (IR). The front-end consists of three phases: lexical, syntactic, and semantic analysis. Front-end compilers perform the following functions:
For Front-end development, the ShuraCore team applies design patterns, data structures, and generally accepted formal language structures. Tools, technologies, and programming languages that we use when developing Front-end:
ShuraCore collaborates with academia, the open-source community, and industry partners to enable us to develop and deliver versatile Front-end compilers to our customers.
Middle-end compilers are used to optimize and analyze software source code. The range of compiler analysis and optimization has many functional differences. The scope of a middle-end compiler can range from a function to full software. ShuraCore development team specializes in the following areas of middle-end compilers:
Optimizing compilers are the backbone of modern software. Optimizers allow you to transform code developed in a popular programming language into code that can run efficiently on hardware. Optimizing compilers ensures that the customer’s developed software performs the same functions faster and uses fewer hardware resources. Optimizing compilers allows using various methods to obtain more optimal program code while maintaining its functionality. Customers most often set the following optimization goals:
Distinguish between low-level and high-level optimization. Low-level optimization transforms the program at the elementary instructions level, for example, instructions of a processor of a specific architecture (ARM, RISC-V, etc.). High-level optimization is carried out at the program’s structural elements, such as modules, functions, branches, and loops.
ShuraCore provides a low-level and high-level optimization service. At the stages of developing an optimizing compiler, the ShuraCore team, together with the customer, analyzes the input requirements, develops a detailed plan of cooperation, taking into account the chosen final solution.
Analyzers are a class of products designed for developed software, applications, and plug-ins. Analyzers are used to detect undeclared features or errors that attackers can exploit for fraud, sabotage, or unauthorized access to information. Existing programming languages have different syntax and semantics; therefore, it is impossible to develop a universal software analysis solution. There is a wide range of excellent tools for analyzing software source code for popular programming languages such as C++, Java, and C#. Simultaneously, the IEC-61131 programming language, HDL language class, and other less popular or highly specialized programming languages do not have a universal code analysis solution. For the quality of the final product, which is based on a highly technical solution, it is necessary to create a code analyzer to eliminate all possible errors. It is often unnecessary to check all the code entirely for specific software, but it must contain only particular rules or requirements.
ShuraCore team is ready to develop a tool to analyze your software solutions while providing a high service level and focus on results.
The back-end compiler is responsible for specific optimization for the processor architecture and code generation for a particular architecture. Back-end design is not a trivial process. The design consists of several phases that are performed to form a binary file for the target architecture. When designing a back-end compiler, it is common to distinguish the following steps for the target processor architecture:
In developing the back-end compiler, the ShuraCore team uses the LLVM and GCC infrastructure. Our company develops back-end compilers for various processor architectures. We provide a service for the adaptation and creation of back-end compilers for existing processor architectures (RISC-V, ARM, PowerPC, etc.) and developed architectures.
The MLIR (Multilevel Intermediate View) project is a new approach to building a reusable and extensible compiler infrastructure. MLIR aims to address software fragmentation, improve compilation for heterogeneous hardware, significantly reduce the cost of building domain-specific compilers, and merge existing compilers. MLIR is designed for hybrid intermediate representation (IR) to support multiple different requirements in a single infrastructure.
The MLIR project defines a standard IR that brings together the infrastructure needed to run high-performance machine learning models in TensorFlow and similar ML environments. This project includes the application of HPC techniques and the integration of search algorithms such as reinforcement learning. MLIR aims to reduce the cost of new hardware implementation and improve usability for existing TensorFlow users.
The MLIR (Multilevel Intermediate View) project is a new approach to building a reusable and extensible compiler infrastructure. MLIR aims to address software fragmentation, improve compilation for heterogeneous hardware, significantly reduce the cost of building domain-specific compilers, and merge existing compilers. MLIR is designed for hybrid intermediate representation (IR) to support multiple different requirements in a single infrastructure.
The MLIR project defines a standard IR that brings together the infrastructure needed to run high-performance machine learning models in TensorFlow and similar ML environments. This project includes the application of HPC techniques and the integration of search algorithms such as reinforcement learning. MLIR aims to reduce the cost of new hardware implementation and improve usability for existing TensorFlow users.
MLIR brings together the infrastructure for high-performance ML models in TensorFlow. The TensorFlow ecosystem contains several compilers and optimizers that operate at multiple software and hardware stack levels. We expect the gradual adoption of MLIR to simplify every aspect of this stack. ShuraCore uses the MLIR project to design compilers for the following hardware platforms:
ShuraCore team specializes in using the following frameworks and tools:
HLS (High-Level Synthesis) compilers are used to create digital devices using high-level languages. The main goal of HLS products is to simplify the FPGA and ASIC design process. The most common task of the HLS compiler is to generate the HDL group languages (Verilog or VHDL) from the source code of the high-level languages (C/C++).
Many modern implementations of HLS compilers are done using the LLVM framework. High-level synthesis can be created using high-level design languages for a programmable logic controller (PLC), making the IEC 61131 group languages at the output.
The HLS compiler generates various hardware microarchitectures following the specified directives and taking into account the tools used. HLS compilers allow you to find a trade-off between execution speed and hardware complexity.
Our team is ready to develop an HLS compiler for your tasks. ShuraCore constantly monitors trends in this area of compilers and also collaborates with the academic community. ShuraCore uses HLS in processor architectures, develops many attractive FPGA solutions and other products using HLS.
Hardware compilers, or synthesis tools, are compilers whose output is a description of a hardware configuration instead of a sequence of instructions. The output of these compilers is for hardware. An example of hardware is a field-programmable gate array (FPGA) or structural application-specific integrated circuit (ASIC).
Compilers are called hardware compilers because the source code they compile effectively controls the final hardware configuration. The result of the compilation is the correct interaction of the internal components of the hardware.
Tools, technologies, and programming languages that we use when developing hardware compilers:
We use the following open source solutions to create bitstreams from HDL files:
A virtual machine is a software or hardware system that emulates a particular platform’s hardware and executes programs for a target platform on a host platform or virtualizes a specific venue and creates environments that isolate programs and even operating systems from each other. A virtual machine also refers to the specification of some computing environments.
Virtual machines can be used for:
ShuraCore team uses the following tools and programming languages when developing virtual machines:
An interpreter is a translator whose task is to perform line-by-line analysis, process and execute the program’s source code or request. The interpreter has the advantage of stepping through the code without the need for compilation, which can be useful for running it on embedded platforms.
Our company is engaged in porting interpreters for any hardware and software platforms and AST and Bytecode interpreters’ development.
JIT (Just-in-time) compilers are used to improve the performance of interpreted programs. JIT compilation is about compiling a program into its code while the program is running. This compilation is also known as dynamic compilation. The advantage of a JIT compilation strategy is that it has complete knowledge of the target architecture on which the
The front-end compiler, analyzing the source code, creates an internal representation of the program – an intermediate representation (IR). The front-end consists of three phases: lexical, syntactic, and semantic analysis. Front-end compilers perform the following functions: Character table management; Data structure management; Analyzing the source code and displaying information (location, type, and scope) associated with
Middle-end compilers are used to optimize and analyze software source code. The range of compiler analysis and optimization has many functional differences. The scope of a middle-end compiler can range from a function to full software. ShuraCore development team specializes in the following areas of middle-end compilers: Optimizers Analyzers Optimizers Optimizing compilers are the backbone
The back-end compiler is responsible for specific optimization for the processor architecture and code generation for a particular architecture. Back-end design is not a trivial process. The design consists of several phases that are performed to form a binary file for the target architecture. When designing a back-end compiler, it is common to distinguish the
The MLIR (Multilevel Intermediate View) project is a new approach to building a reusable and extensible compiler infrastructure. MLIR aims to address software fragmentation, improve compilation for heterogeneous hardware, significantly reduce the cost of building domain-specific compilers, and merge existing compilers. MLIR is designed for hybrid intermediate representation (IR) to support multiple different requirements in
Hardware compilers, or synthesis tools, are compilers whose output is a description of a hardware configuration instead of a sequence of instructions. The output of these compilers is for hardware. An example of hardware is a field-programmable gate array (FPGA) or structural application-specific integrated circuit (ASIC). Compilers are called hardware compilers because the source code
A virtual machine is a software or hardware system that emulates a particular platform’s hardware and executes programs for a target platform on a host platform or virtualizes a specific venue and creates environments that isolate programs and even operating systems from each other. A virtual machine also refers to the specification of some computing
An interpreter is a translator whose task is to perform line-by-line analysis, process and execute the program’s source code or request. The interpreter has the advantage of stepping through the code without the need for compilation, which can be useful for running it on embedded platforms. Our company is engaged in porting interpreters for any
HLS (High-Level Synthesis) compilers are used to create digital devices using high-level languages. The main goal of HLS products is to simplify the FPGA and ASIC design process. The most common task of the HLS compiler is to generate the HDL group languages (Verilog or VHDL) from the source code of the high-level languages (C/C++). Many modern implementations of HLS compilers
The LLVM Project is a collection of modular and reusable compiler and toolchain technologies. Despite its name, LLVM has little to do with traditional virtual machines. The word “LLVM” itself is not an acronym. It is the full name of the project. LLVM and the GNU Compiler Collection (GCC) are compilers. The difference is that