Composable accelerator-rich microprocessor enhanced for adaptivity and longevity

Abstract Accelerator-rich platforms demonstrate orders of magnitude improvement in performance and energy efficiency over software, yet they lack adaptivity to new algorithms and can see low accelerator utilization. To address these issues we propose CAMEL: Composable Accelerator-rich Microprocessor Enhanced for Longevity. CAMEL features programmable fabric (PF) to extend the use of ASIC composable accelerators in supporting algorithms that are beyond the scope of the baseline platform. Using a combination of hardware extensions and compiler support, we demonstrate on average 11.6X performance improvement and 13.9X energy savings across benchmarks that deviate from the original domain for our baseline platform

The effect of NAFLD (non-alcoholic fatty liver disease) on long-term outcome of chronic hepatitis B in Iranian patients

ABSTRAC

Equivalence checking of arithmetic expressions using fast evaluation

Arithmetic expressions are the fundamental building blocks of hardware and software systems. An important problem in computational theory is to decide if two arithmetic expressions are equivalent. However, the general problem of equivalence checking, in digital computers, belongs to the NP Hard class of problems. Moreover, existing general techniques for solving this decision problem are applicable to very simple expressions and impractical when applied to more complex expressions found in programs written in high-level languages. In this paper we propose a method for solving the arithmetic expression equivalence problem using partial evaluation. In particular, our technique is specifically designed to solve the problem of equivalence checking of arithmetic expressions obtained from high-level language descriptions of hardware/software systems, which consists of regular arithmetic operators (+, −, ×) and logical operators (and, or, not). In our method, we use interval analysis to substantially prune the domain space of arithmetic expressions and limit the evaluation effort to a sufficiently limited set of subspaces. Our results show that the proposed method is fast enough to be of use in practice

Expression equivalence checking using interval analysis

Arithmetic expressions are the fundamental building blocks of hardware and software systems. An important problem in computational theory is to decide if two arithmetic expressions are equivalent. However, the general problem of equivalence checking, in digital computers, belongs to the NP Hard class of problems. Moreoever, existing general techniques for solving this decision problem are applicable to very simple expressions and impractical when applied to more complex expressions found in programs written in high-level languages. In this paper we propose a method for solving the arithmetic expression equivalence problem using partial evaluation. In particular, our technique is specifically designed to solve the problem of equivalence checking of arithmetic expressions obtained from high-level language descriptions of hardware/software systems. In our method, we use interval analysis to substantially prune the domain space of arithmetic expressions and limit the evaluation efforts to a sufficiently limited set of subspaces. Our results show that the proposed method is fast enough to be of use in practice

Optimizing control flow in loops using interval and dependence analysis

We present a novel loop transformation technique, particularly well suited for optimizing embedded compilers, where an increase in compilation time is acceptable in exchange for significant performance increase. The transformation technique optimizes loops containing nested conditional blocks. Specifically, the transformation takes advantage of the fact that the Boolean value of the conditional expression, determining the true/false paths, can be statically analyzed using a novel interval analysis technique that can evaluate conditional expressions in the general polynomial form. Results from interval analysis combined with loop dependency information is used to partition the iteration space of the nested loop. In such cases, the loop nest is decomposed such as to eliminate the conditional test, thus substantially reducing the execution time. Our technique completely eliminates the conditional from the loops (unlike previous techniques) thus further facilitating the application of other optimizations and improving the overall speedup. Applying the proposed transformation technique on loop kernels taken from Mediabench, SPEC-2000, mpeg4, qsdpcm and gimp, on average we measured a 2.34X speedup when running on a UltraSPARC processor, a 2.92X speedup when running on an Intel Core Duo processor, a 2.44X speedup when running on a PowerPC G5 processor and a 2.04X speedup when running on an ARM9 processor. Performance improvement, taking the entire application into account, was also promising: for 3 selected applications (mpeg-enc, mpeg-dec and qsdpcm) we measured 15% speedup on best case (5% on average) for the whole application

Expression equivalence checking using interval analysis

Arithmetic expressions are the fundamental building blocks of hardware and software systems. An important problem in computational theory is to decide if two arithmetic expressions are equivalent. However, the general problem of equivalence checking, in digital computers, belongs to the NP Hard class of problems. Moreover, existing general techniques for solving this decision problem are applicable to very simple expressions and impractical when applied to more complex expressions found in programs written in high-level languages. In this paper, we propose a method for solving the arithmetic expression equivalence problem using partial evaluation. In particular, our technique is specifically designed to solve the problem of equivalence checking of arithmetic expressions obtained from high-level language descriptions of hardware/software systems. In our method, we use interval analysis to substantially prune the domain space of arithmetic expressions and limit the evaluation effort to a sufficiently limited set of subspaces. Our results show that the proposed method is fast enough to be of use in practice

Control Flow Optimization in Loops using Interval Analysis

We present a novel loop transformation technique, particularly well suited for optimizing embedded compilers, where an increase in compilation time is acceptable in exchange for significant performance increase. The transformation technique optimizes loops containing nested conditional blocks. Specifically, the transformation takes advantage of the fact that the Boolean value of the conditional expression, determining the true/false paths, can be statically analyzed using a novel interval analysis technique that can evaluate conditional expressions in the general polynomial form. Results from interval analysis combined with loop dependency information is used to partition the iteration space of the nested loop. In such cases, the loop nest is decomposed such as to eliminate the conditional test, thus substantially reducing the execution time. Our technique completely eliminates the conditional from the loops (unlike previous techniques) thus further facilitating the application of other optimizations and improving the overall speedup. Applying the proposed transformation technique on loop kernels taken from Mediabench, SPEC-2000, mpeg4, qsdpcm and gimp, on average we measured a 175 % (1.75X) improvement of execution time when running on a SPARC processor, a 336 % (4.36X) improvement of execution time when running on an Intel Core Duo processor and a 198.9 % (2.98X) improvement of execution time when running on a PowerPC G5 processor

Optimizing control flow in loops using interval and dependence analysis

We present a novel loop transformation technique, particularly well suited for optimizing embedded compilers, where an increase in compilation time is acceptable in exchange for significant performance increase. The transformation technique optimizes loops containing nested conditional blocks. Specifically, the transformation takes advantage of the fact that the Boolean value of the conditional expression, determining the true/false paths, can be statically analyzed using a novel interval analysis technique that can evaluate conditional expressions in the general polynomial form. Results from interval analysis combined with loop dependency information is used to partition the iteration space of the nested loop. In such cases, the loop nest is decomposed such as to eliminate the conditional test, thus substantially reducing the execution time. Our technique completely eliminates the conditional from the loops (unlike previous techniques) thus further facilitating the application of other optimizations and improving the overall speedup. Applying the proposed transformation technique on loop kernels taken from Mediabench, SPEC-2000, mpeg4, qsdpcm and gimp, on average we measured a 2.34X speedup when running on a UltraSPARC processor, a 2.92X speedup when running on an Intel Core Duo processor, a 2.44X speedup when running on a PowerPC G5 processor and a 2.04X speedup when running on an ARM9 processor. Performance improvement, taking the entire application into account, was also promising: for 3 selected applications (mpeg-enc, mpeg-dec and qsdpcm) we measured 15% speedup on best case (5% on average) for the whole application

5B-5 Short-Circuit Compiler Transformation: Optimizing Conditional Blocks

Abstract — We present the short-circuit code transformation technique, intended for embedded compilers. The transformation technique optimizes conditional blocks in high-level programs. Specifically, the transformation takes advantage of the fact that the Boolean value of the conditional expression, determining the true/false paths, can be statically analyzed to determine cases when one or the other of the true/false paths are guaranteed to execute. In such cases, code is generated to bypass the evaluation of the conditional expression. In instances when the bypass code is faster to evaluate than the conditional expression, a net performance gain is obtained. Our experiments with the Mediabench applications show that the short-circuit transformation yields a an average of 35.1 % improvement in execution time for SPARC and an average of 36.3 % improvement in execution time for ARM. We also measured an average of 36.4 % reduction in power consumption for ARM. I