Memory Mangement in the PoSSo Solver

AbstractA uniform general purpose garbage collector may not always provide optimal performance. Sometimes an algorithm exhibits a predictable pattern of memory usage that could be exploited, delaying as much as possible the intervention of the collector. This requires a collector whose strategy can be customized to the need of an algorithm. We present a dynamic memory management framework which allows such customization, while preserving the convenience of automatic collection in the normal case. The Customizable Memory Management (CMM) organizes memory in multiple heaps, each one encapsulating a particular storage discipline. The default heap for collectable objects uses the technique of mostly copying garbage collection, providing good performance and memory compaction. Customization of the collector is achieved through object orientation by specialising the collector methods for each heap class. We describe how the CMM has been exploited in the implementation of the Buchberger algorithm, by using a special heap for temporary objects created during polynomial reduction. The solution drastically reduces the overall cost of memory allocation in the algorithm

Designing efficient and safe weak references in Eiffel with parametric types

Rapport interne.In this paper, we present our work on the design and implementation of weak references within the SmartEiffel project. We introduce the known concept of weak references, reminding how this peculiar kind of references can be used to optimize and fine-tune the memory behavior of programs, thus potentially speeding up their execution. We show that genericity (parametric types in Eiffel) is the key to implementing weak references in a statically-checked hence safer and more efficient way. We compare our solution for weak references to similar notions in other languages and stress the advantages it offers

Subheap-Augmented Garbage Collection

Automated memory management avoids the tedium and danger of manual techniques. However, as no programmer input is required, no widely available interface exists to permit principled control over sometimes unacceptable performance costs. This dissertation explores the idea that performance-oriented languages should give programmers greater control over where and when the garbage collector (GC) expends effort. We describe an interface and implementation to expose heap partitioning and collection decisions without compromising type safety. We show that our interface allows the programmer to encode a form of reference counting using Hayes\u27 notion of key objects. Preliminary experimental data suggests that our proposed mechanism can avoid high overheads suffered by tracing collectors in some scenarios, especially with tight heaps. However, for other applications, the costs of applying subheaps---in human effort and runtime overheads---remain daunting

Algoritam za zbrinjavanje memorije s označavanjem i smanjenim oslobađanjem

In this paper two simple improvements over traditional mark-sweep collector are proposed. The core idea is placing small objects of the same type in buckets. The buckets are organised in such way to eliminate the internal fragmentation, sweeping, and freeing inside them. The measured improvement of garbage collection time over traditional mark-sweep is 19%. Another proposed improvement is more general and is applicable to other garbage collection algorithms as well. It uses heuristics to control the heap growth. The regularities in behaviour of objects of particular types are used to determine whether the collection should be performed or avoided in favour of immediate heap expansion. The heap expansion algorithm reduces garbage collection time over traditional mark-sweep for 49% while keeping the heap size approximately the same.U ovom članku opisana su dva jednostavna poboljšanja algoritma označi-oslobodi. Osnovna ideja jest smještanje malih objekata istog tipa u pretince. Pretinci su organizirani tako da se u njima ne pojavljuje unutarnja fragmentacija, a uklanja se i potreba za oslobađanjem blokova zauzetih nedohvatljivim objektima. Vrijeme provedeno u zbrinjavanju manje je za 19% u odnosu na klasični algoritam označi-oslobodi. Drugo poboljšanje je općenitije i moguće ga je primijeniti i na druge algoritme za zbrinjavanje memorije. U njemu rastom gomile upravlja heuristički algoritam koji koristi pravilnosti u ponašanju objekata različitih tipova. Na temelju njih, algoritam odlučuje hoće li gomila biti zbrinuta ili odmah proširena. Heuristička inačica algoritma smanjuje vrijeme provedeno u zbrinjavanju u odnosu na tradicionalni algoritam označi-oslobodi za 49%, a da pri tome zahtijeva približno istu količinu memorije

SPICE²: A Spatial, Parallel Architecture for Accelerating the Spice Circuit Simulator

Spatial processing of sparse, irregular floating-point computation using a single FPGA enables up to an order of magnitude speedup (mean 2.8X speedup) over a conventional microprocessor for the SPICE circuit simulator. We deliver this speedup using a hybrid parallel architecture that spatially implements the heterogeneous forms of parallelism available in SPICE. We decompose SPICE into its three constituent phases: Model-Evaluation, Sparse Matrix-Solve, and Iteration Control and parallelize each phase independently. We exploit data-parallel device evaluations in the Model-Evaluation phase, sparse dataflow parallelism in the Sparse Matrix-Solve phase and compose the complete design in streaming fashion. We name our parallel architecture SPICE²: Spatial Processors Interconnected for Concurrent Execution for accelerating the SPICE circuit simulator. We program the parallel architecture with a high-level, domain-specific framework that identifies, exposes and exploits parallelism available in the SPICE circuit simulator. This design is optimized with an auto-tuner that can scale the design to use larger FPGA capacities without expert intervention and can even target other parallel architectures with the assistance of automated code-generation. This FPGA architecture is able to outperform conventional processors due to a combination of factors including high utilization of statically-scheduled resources, low-overhead dataflow scheduling of fine-grained tasks, and overlapped processing of the control algorithms. We demonstrate that we can independently accelerate Model-Evaluation by a mean factor of 6.5X(1.4--23X) across a range of non-linear device models and Matrix-Solve by 2.4X(0.6--13X) across various benchmark matrices while delivering a mean combined speedup of 2.8X(0.2--11X) for the two together when comparing a Xilinx Virtex-6 LX760 (40nm) with an Intel Core i7 965 (45nm). With our high-level framework, we can also accelerate Single-Precision Model-Evaluation on NVIDIA GPUs, ATI GPUs, IBM Cell, and Sun Niagara 2 architectures. We expect approaches based on exploiting spatial parallelism to become important as frequency scaling slows down and modern processing architectures turn to parallelism (\eg multi-core, GPUs) due to constraints of power consumption. This thesis shows how to express, exploit and optimize spatial parallelism for an important class of problems that are challenging to parallelize.</p

Comparative Analysis of Widely use Object-Oriented Languages

Programming is an integral part of computer science discipline. Every day the programming environment is not only rapidly growing but also changing and languages are constantly evolving. Learning of object-oriented paradigm is compulsory in every computer science major so the choice of language to teach object-oriented principles is very important. Due to large pool of object-oriented languages, it is difficult to choose which should be the first programming language in order to teach object-oriented principles. Many studies shown which should be the first language to tech object-oriented concepts but there is no method to compare and evaluate these languages. In this article we proposed a comprehensive framework to evaluate the widely used object-oriented languages. The languages are evaluated basis of their technical and environmental features.Comment: 30 pages, figures