The hArtes Tool Chain

This chapter describes the different design steps needed to go from legacy code to a transformed application that can be efficiently mapped on the hArtes platform

An Efficient Platform for the Automatic Extraction of Patterns in Native Code

Different software tools, such as decompilers, code quality analyzers, recognizers of packed executable files, authorship analyzers, and malware detectors, search for patterns in binary code. The use of machine learning algorithms, trained with programs taken from the huge number of applications in the existing open source code repositories, allows finding patterns not detected with the manual approach. To this end, we have created a versatile platform for the automatic extraction of patterns from native code, capable of processing big binary files. Its implementation has been parallelized, providing important runtime performance benefits for multicore architectures. Compared to the single-processor execution, the average performance improvement obtained with the best configuration is 3.5 factors over the maximum theoretical gain of 4 factors

Automatic design of domain-specific instructions for low-power processors

This paper explores hardware specialization of low­ power processors to improve performance and energy efficiency. Our main contribution is an automated framework that analyzes instruction sequences of applications within a domain at the loop body level and identifies exactly and partially-matching sequences across applications that can become custom instructions. Our framework transforms sequences to a new code abstraction, a Merging Diagram, that improves similarity identification, clusters alike groups of potential custom instructions to effectively reduce the search space, and selects merged custom instructions to efficiently exploit the available customizable area. For a set of 11 media applications, our fast framework generates instructions that significantly improve the energy-delay product and speed­ up, achieving more than double the savings as compared to a technique analyzing sequences within basic blocks. This paper shows that partially-matched custom instructions, which do not significantly increase design time, are crucial to achieving higher energy efficiency at limited hardware areas

Metoda projektovanja namenskih programabilnih hardverskih akceleratora

Namenski računarski sistemi se najčesće projektuju tako da mogu da podrže izvršavanje većeg broja željenih aplikacija. Za postizanje što veće efikasnosti, preporučuje se korišćenje specijalizovanih procesora Application Specific Instruction Set Processors–ASIPs, na kojima se izvršavanje programskih instrukcija obavlja u za to projektovanim i nezavisnimhardverskim blokovima (akceleratorima). Glavni razlog za postojanje nezavisnih akceleratora jeste postizanjemaksimalnog ubrzanja izvršavanja instrukcija. Me ¯ dutim, ovakav pristup podrazumeva da je za svaki od blokova potrebno projektovati integrisano (ASIC) kolo, čime se bitno povećava ukupna površina procesora. Metod za smanjenje ukupne površine jeste primena DatapathMerging tehnike na dijagrame toka podataka ulaznih aplikacija. Kao rezultat, dobija se jedan programabilni hardverski akcelerator, sa mogućnosću izvršavanja svih željenih instrukcija. Međutim, ovo ima negativne posledice na efikasnost sistema. često se zanemaruje činjenica da, usled veoma ograničene fleksibilnosti ASIC hardverskih akceleratora, specijalizovani procesori imaju i drugih nedostataka. Naime, u slučaju izmena, ili prosto nadogradnje, specifikacije procesora u završnimfazama projektovanja, neizbežna su velika kašnjenja i dodatni troškovi promene dizajna. U ovoj tezi je pokazano da zahtevi za fleksibilnošću i efikasnošću ne moraju biti međusobno isključivi. Demonstrirano je je da je moguce uneti ograničeni nivo fleksibilnosti hardvera tokom dizajn procesa, tako da dobijeni hardverski akcelerator može da izvršava ne samo aplikacije definisane na samom početku projektovanja, već i druge aplikacije, pod uslovom da one pripadaju istom domenu. Drugim rečima, u tezi je prezentovana metoda projektovanja fleksibilnih namenskih hardverskih akceleratora. Eksperimentalnom evaluacijom pokazano je da su tako dobijeni akceleratori u većini slučajeva samo do 2 x veće površine ili 2 x većeg kašnjenja od akceleratora dobijenih primenom DatapathMerging metode, koja pritom ne pruža ni malo dodatne fleksibilnosti.Typically, embedded systems are designed to support a limited set of target applications. To efficiently execute those applications, they may employ Application Specific Instruction Set Processors (ASIPs) enriched with carefully designed Instructions Set Extension (ISEs) implemented in dedicated hardware blocks. The primary goal when designing ISEs is efficiency, i.e. the highest possible speedup, which implies synthesizing all critical computational kernels of the application dataflow graphs as an Application Specific Integrated Circuit (ASICs). Yet, this can lead to high on-chip area dedicated solely to ISEs. One existing approach to decrease this area by paying a reasonable price of decreased efficiency is to perform datapath merging on input dataflow graphs (DFGs) prior to generating the ASIC. It is often neglected that even higher costs can be accidentally incurred due to the lack of flexibility of such ISEs. Namely, if late design changes or specification upgrades happen, significant time-to-market delays and nonrecurrent costs for redesigning the ISEs and the corresponding ASIPs become inevitable. This thesis shows that flexibility and efficiency are not mutually exclusive. It demonstrates that it is possible to introduce a limited amount of hardware flexibility during the design process, such that the resulting datapath is in fact reconfigurable and thus can execute not only the applications known at design time, but also other applications belonging to the same application-domain. In other words, it proposes a methodology for designing domain-specific reconfigurable arrays out of a limited set of input applications. The experimental results show that resulting arrays are usually around 2£ larger and 2£ slower than ISEs synthesized using datapath merging, which have practically null flexibility beyond the design set of DFGs

Libra: Achieving Efficient Instruction- and Data- Parallel Execution for Mobile Applications.

Mobile computing as exemplified by the smart phone has become an integral part of our daily lives. The next generation of these devices will be driven by providing richer user experiences and compelling capabilities: higher definition multimedia, 3D graphics, augmented reality, and voice interfaces. To meet these goals, the core computing capabilities of the smart phone must be scaled. But, the energy budgets are increasing at a much lower rate, thus fundamental improvements in computing efficiency must be garnered. To meet this challenge, computer architects employ hardware accelerators in the form of SIMD and VLIW. Single-instruction multiple-data (SIMD) accelerators provide high degrees of scalability for applications rich in data-level parallelism (DLP). Very long instruction word (VLIW) accelerators provide moderate scalability for applications with high degrees of instruction-level parallelism (ILP). Unfortunately, applications are not so nicely partitioned into two groups: many applications have some DLP, but also contain significant fractions of code with low trip count loops, complex control/data dependences, or non-uniform execution behavior for which no DLP exists. Therefore, a more adaptive accelerator is required to be able to deploy resources as needed: exploit DLP on SIMD when it’s available, but fall back to ILP on the same hardware when necessary. In this thesis, we first focus on various compiler solutions that solve inefficiency problem in both VLIW and SIMD accelerators. For SIMD accelerators, a new vectorization pass, called SIMD Defragmenter, is introduced to uncover hidden DLP using subgraph identification in SIMD accelerators. CGRA express effectively accelerates sequential code regions using a bypass network in VLIW accelerators, and Resource Recycling leverages stream-graph modulo scheduling technique for scheduling of multiple code regions in multi-core accelerators. Second, we propose the new scalable multicore accelerator referred to as Libra for mobile systems, which can support execution of code regions having both DLP and ILP, as well as hybrid combinations of the two. We believe that as industry requires higher performance, the proposed flexible accelerator and compiler support will put more resources to work in order to meet the performance and power efficiency requirements.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99840/1/yjunpark_1.pd