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

CREATING AVAILABLE BANDWIDTH HEATMAP FOR USER ASSIST TO RELOCATE BASED ON BANDWIDTH NEEDS

A solution is presented herein for which an end-user of a wireless network does not know the channel utilization/interference conditions at a given location and also which location to go to meet their bandwidth needs. This solution provides a way to calculate the available bandwidth heatmap for a given floor map and a way for the user to visualize it using a mobile app. This solution also gives options to the user and provides a wayfinding solution to physically move to an area of better available bandwidth

Evaluating the LRFD Factor for Cold-formed Steel Compression Members

This paper summarizes recent work to determine if the LRFD resistance factor for cold-formed steel compression member s can be increased above its current value of φ c =0.85. An experimental database of 675 concentrically loaded columns with plain and lipped C-sections, plain and lipped Z-sections, hat sections and angle sections, including members with holes was compiled. The predicted strength of each specimen was calculated with the AISI-S100-07 Main Specification and Direct Strength Method (DSM). Test-to-predicted strength statistics were employed with the first order second moment reliability approach in AISI-S100-07 Chapter F to calculate the resistance factors. The observed trends demonstrate that DSM is a more accurate strength predictor than the current Main Specifica tion, especially for columns with partially effective cross sections. Serious consideration should be given to replacing the Main Specification with DSM, which would provide improved prediction accuracy and a viable rationale for increasing the resistance factor. The test-to-predicted strength ratios for columns with plain and lipped angle cross-sections exhibit a high coefficient of variation and b ecome increasingly conservative with increasing global slenderness. Fundamen tal research on the mechanics of angle compression members is needed to improve existing design methods

Functional outcome of minimally invasive posterior stabilisation in dorsal and lumbar spine fractures

This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Outcome analysis of surgically managed unstable burst fracture

Background:Burst fractures are common injuries of dorsolumbar spine. In indicated cases, surgery is the treatment of choice. Significant controversy exists regarding surgical intervention for these fractures. Posterior decompression, anterior decompression and instrumentation, and combined anterior decompression and posterior instrumentation have been recommended in various studies. Here we are going to evaluate unstable burst fractures of thoracic and lumbar spine treated by isolated anterior decompression and instrumented fusion with TSM-Bone graft composite.Methods: Prospective study of thirty-six cases of unstable fracture of thoracic and lumbar spine treated in Sri Ramachandra Medical centre from January 2011 to January 2014. The inclusion criteria were burst fractures of thoracic or lumbar spine complete or incomplete neurological deficit and burst fractures of thoracic or lumbar spine without neurological deficit but with mechanical instability. The exclusion criteria were pathological fractures, chance fracture, stable burst, wedge compression and osteoporotic compression fractures. The results were analyzed during the follow-up using the Pain – Visual analogue scale, Fusion status and radiographic parameter – K-angle .For pain score were given as 3,2,1 for absent, moderate and severe pain respectively. Regarding fusion status score of 3,2,1 were given when fusion was good, fair and no sign of fusion respectively.Results:Mean pre-operative K-angle was 28o. Average loss of correction at final follow up was 3o.Mean correction of K-angle was 140.Moderate to severe loss of correction of K- angle was observed in 4 patients. Mild to moderate pain in 5 patients treated with analgesics. Average TSM subsidence was 3mm.Conclusions:Bone graft composite provides stable biomechanical support to deficient anterior column in burst fractures and allows early rehabilitation and mobilization. Neural recovery may occur after anterior decompression, stabilization and fusion with TSM-Bone graft composite in dorsolumbar burst fractures with incomplete cord injury

Electromagnetic interference shielding effectiveness of copper plated fabrics

Electroless plating of copper on cotton and polyester fabrics has been done with varying CuSO4 concentration (8, 12, 16 and 20 g/L) and temperature (30°, 40°, 50° & 60° C) for 30min at all levels. The plating depositions are characterized by scanning electron microscope and X-ray diffraction respectively. The physical properties, such as tensile strength, tear strength, abrasion resistance and electromagnetic interference shielding performances have also been investigated. It is found that the tensile and tear strength of cotton and polyester fabrics decrease with the increase in CuSO4 concentration. The abrasion resistance of copper plated cotton fabric decreases more than that of polyester fabric. The surface resistance of the copper plated polyester fabric shows poor electrical resistance and the electromagnetic interference shielding effectiveness, but has high shielding effectiveness up to 30dB than cotton fabrics

BlackJack: Secure machine learning on IoT devices through hardware-based shuffling

Neural networks are seeing increased use in diverse Internet of Things (IoT) applications such as healthcare, smart homes and industrial monitoring. Their widespread use makes neural networks a lucrative target for theft. An attacker can obtain a model without having access to the training data or incurring the cost of training. Also, networks trained using private data (e.g., medical records) can reveal information about this data. Networks can be stolen by leveraging side channels such as power traces of the IoT device when it is running the network. Existing attacks require operations to occur in the same order each time; an attacker must collect and analyze several traces of the device to steal the network. Therefore, to prevent this type of attack, we randomly shuffle the order of operations each time. With shuffling, each operation can now happen at many different points in each execution, making the attack intractable. However, we show that shuffling in software can leak information which can be used to subvert this solution. Therefore, to perform secure shuffling and reduce latency, we present BlackJack, hardware added as a functional unit within the CPU. BlackJack secures neural networks on IoT devices by increasing the time needed for an attack to centuries, while adding just 2.46% area, 3.28% power and 0.56% latency overhead on an ARM M0+ SoC.Comment: 16 pages, 6 figure