While many approximate computing methods are quite application-dependent, reducing the size of the data representation used in the computation has a more general applicability. We present a tuning assistant for floating to fixed point optimization (TAFFO), an LLVM-based framework designed to assist programmers in the precision tuning of software. We discuss the framework architecture and we provide guidelines to effectively tradeoff precision to improve the time-to-solution. We evaluate our framework on a well-known approximate computing benchmark suite, AXBENCH, achieving a speedup on 5 out of 6 benchmarks (up to 366%) with only a limited loss in precision
Approximating ideal program outputs is a common technique for solving computationally difficult pro...
Precision tuning consists of finding the least floating-point formats enabling a program to compute ...
Approximating ideal program outputs is a common technique for solving computationally difficult prob...
While many approximate computing methods are quite application-dependent, reducing the size of the d...
Precision tuning is an emerging class of techniques that leverage the trade-off between accuracy and...
We present taffo, a framework that automatically performs precision tuning to exploit the performanc...
Many classes of applications, both in the embedded and high performance domains, can trade off the a...
Approximate computing has seen significant interest as a design philosophy oriented to performance a...
While tremendously useful, automated techniques for tuning the precision of floating-point programs ...
<p>In this thesis, we design frameworks for efficient and accurate floating point computation. The p...
Given the variety of numerical errors that can occur, floating-point programs are difficult to write...
Nowadays, parallel applications are used every day in high performance computing, scientific computi...
Approximate computing frameworks configure applications so they can operate at a range of points in ...
The floating-point numbers used in computer programs are a finite approximation of real numbers. In ...
Approximating ideal program outputs is a common technique for solving computationally difficult pro...
Precision tuning consists of finding the least floating-point formats enabling a program to compute ...
Approximating ideal program outputs is a common technique for solving computationally difficult prob...
While many approximate computing methods are quite application-dependent, reducing the size of the d...
Precision tuning is an emerging class of techniques that leverage the trade-off between accuracy and...
We present taffo, a framework that automatically performs precision tuning to exploit the performanc...
Many classes of applications, both in the embedded and high performance domains, can trade off the a...
Approximate computing has seen significant interest as a design philosophy oriented to performance a...
While tremendously useful, automated techniques for tuning the precision of floating-point programs ...
<p>In this thesis, we design frameworks for efficient and accurate floating point computation. The p...
Given the variety of numerical errors that can occur, floating-point programs are difficult to write...
Nowadays, parallel applications are used every day in high performance computing, scientific computi...
Approximate computing frameworks configure applications so they can operate at a range of points in ...
The floating-point numbers used in computer programs are a finite approximation of real numbers. In ...
Approximating ideal program outputs is a common technique for solving computationally difficult pro...
Precision tuning consists of finding the least floating-point formats enabling a program to compute ...
Approximating ideal program outputs is a common technique for solving computationally difficult prob...