Compiler-directed Shared-Memory Communication for Iterative Parallel Applications

Many scientific applications are iterative and specify repetitive communication patterns. This paper shows how a parallel-language compiler and a predictive cache-coherence protocol in a distributed shared memory system together can implement shared-memory communication efficiently for applications with unpredictable but repetitive communication patterns. The compiler uses static analysis to identify program points where potentially repetitive communication occurs. At runtime, the protocol builds a communication schedule in one iteration and uses the schedule to pre-send data in subsequent iterations. This paper contains measurements of three iterative applications (including adaptive programs with unstructured data accesses) that show that a predictive protocol increases the number of shared-data requests satisfied locally, thus reducing the remote data access latency and total execution time

Compiler-directed Shared-Memory Communication for Iterative Parallel Applications

Many scientific applications are iterative and specify repetitive communication patterns. This paper shows how a parallel-language compiler and a predictive cachecoherence protocol in a distributed shared memory system together can implement shared-memory communication efficiently for applications with unpredictable but repetitive communication patterns. The compiler uses static analysis to identify program points where potentially repetitive communication occurs. At runtime, the protocol builds a communication schedule in one iteration and uses the schedule to pre-send data in subsequent iterations. This paper contains measurements of three iterative applications (including adaptive programs with unstructured data accesses) that show that a predictive protocol increases the number of shared-data requests satisfied locally, thus reducing the remote data access latency and total execution time. This work is supported in part by Wright Laboratory Avionics Directorate, Air Force Materi..

Automatic generation of synthetic workloads for multicore systems

textWhen designing a computer system, benchmark programs are used with cycle accurate performance/power simulators and HDL level simulators to evaluate novel architectural enhancements, perform design space exploration, understand the worst-case power characteristics of various designs and find performance bottlenecks. This research effort is directed towards automatically generating synthetic benchmarks to tackle three design challenges: 1) For most of the simulation related purposes, full runs of modern real world parallel applications like the PARSEC, SPLASH suites cannot be used as they take machine weeks of time on cycle accurate and HDL level simulators incurring a prohibitively large time cost 2) The second design challenge is that, some of these real world applications are intellectual property and cannot be shared with processor vendors for design studies 3) The most significant problem in the design stage is the complexity involved in fixing the maximum power consumption of a multicore design, called the Thermal Design Power (TDP). In an effort towards fixing this maximum power consumption of a system at the most optimal point, designers are used to hand-crafting possible code snippets called power viruses. But, this process of trying to manually write such maximum power consuming code snippets is very tedious. All of these aforementioned challenges has lead to the resurrection of synthetic benchmarks in the recent past, serving as a promising solution to all the challenges. During the design stage of a multicore system, availability of a framework to automatically generate system-level synthetic benchmarks for multicore systems will greatly simplify the design process and result in more confident design decisions. The key idea behind such an adaptable benchmark synthesis framework is to identify the key characteristics of real world parallel applications that affect the performance and power consumption of a real program and create synthetic executable programs by varying the values for these characteristics. Firstly, with such a framework, one can generate miniaturized synthetic clones for large target (current and futuristic) parallel applications enabling an architect to use them with slow low-level simulation models (e.g., RTL models in VHDL/Verilog) and helps in tailoring designs to the targeted applications. These synthetic benchmark clones can be distributed to architects and designers even if the original applications are intellectual property, when they are not publicly available. Lastly, such a framework can be used to automatically create maximum power consuming code snippets to be able to help in fixing the TDP, heat sinks, cooling system and other power related features of the system. The workload cloning framework built using the proposed synthetic benchmark generation methodology is evaluated to show its superiority over the existing cloning methodologies for single-core systems by generating miniaturized clones for CPU2006 and ImplantBench workloads with only an average error of 2.9% in performance for up to five orders of magnitude of simulation speedup. The correlation coefficient predicting the sensitivity to design changes is 0.95 and 0.98 for performance and power consumption. The proposed framework is evaluated by cloning parallel applications implemented based on p-threads and OpenMP in the PARSEC benchmark suite. The average error in predicting performance is 4.87% and that of power consumption is 2.73%. The correlation coefficient predicting the sensitivity to design changes is 0.92 for performance. The efficacy of the proposed synthetic benchmark generation framework for power virus generation is evaluation on SPARC, Alpha and x86 ISAs using full system simulators and also using real hardware. The results show that the power viruses generated for single-core systems consume 14-41% more power compared to MPrime on SPARC ISA. Similarly, the power viruses generated for multicore systems consume 45-98%, 40-89% and 41-56% more power than PARSEC workloads, running multiple copies of MPrime and multithreaded SPECjbb respectively.Electrical and Computer Engineerin

COMPILER TECHNIQUES FOR EFFICIENT COMMUNICATIONS IN MULTIPROCESSOR SYSTEMS

Technical advances have brought circuit switching back to the stage of interconnection network design for high performance computing. Although circuit switching has long connection establishment delays and the dedication of connections prevents other communicating nodes from sharing the network, it has simple control logic and significant cost advantage over packet or wormhole switching. With the proper assistance from compilers, circuit switching has the potential of providing significant performance benefits when connections can be established prior to the actual communication. This dissertation presents a novel compilation framework for achieving efficient communications in circuit switching interconnection networks. The goal of the framework is to identify communication patterns in Single-Program-Multiple-Data (SPMD) parallel applications and compile these patterns as network configuration directives. This can significantly reduce the communication overhead on circuit switching interconnection networks. A powerful representation scheme is developed in this research to capture the property of communication patterns and allow manipulation of these patterns. Based on the temporal and spatial localities of communications and the capability of the compiler to identify the communication patterns, we classify communication patterns into three categories - static, persistent, and dynamic. We target static and persistent communications, which are dominant in most parallel applications. To identify communication patterns, we develop a novel symbolic expression analysis. We develop certain compiler techniques for analyzing communication patterns. Since the underlying network capacity is limited, we develop an algorithm to partition the program into phases based on the communication requirements and network capacity. To demonstrate the effectiveness of our framework, we implement an experimental compiler. The compiler identifies the communication patterns from the source code, partitions the program into phases, and inserts the network configuration directives at phase boundaries to achieve efficient communications. The compiler also can generate communication traces, which provides useful information about the communication pattern correlated to the structure of the source code. We develop a multiprocessor system simulator to evaluate our techniques. Our simulation-based performance analysis demonstrates that using our compiler techniques can achieve the same level, or even better level of communication performance than fast packet switching networks while using much less expensive circuit switches