11690974
Inferno: a functional simulation infrastructure for modeling microarchitectural data speculations
This paper presents key insights and design rationales behind Inferno, a functional simulation construction framework developed at Intel to support execution-driven cycle-accurate performance modeling and simulation of advanced microarchitectural data speculation techniques for future processor designs and explorations. Inferno divides the task of functional simulation into three essential components, namely: (1) context manager of in-flight speculatively executed instructions, (2) stateless emulator of instruction semantics, and (3) a high speed functional simulator capable of booting OS and running large-scale system workloads. These building block components work together in concert via a set of well-architected functional model convergence APIs. With a novel abstraction called speculative domain, the context manager serves effectively as a relational database about the in-flight instructions and on-going speculations. Through a set of functional model usage APIs, the context manager enables performance models to express arbitrary microarchitectural data speculation scenarios. The contribution of this paper is to demonstrate the importance of providing a functional model with modular construction, proper abstraction and expressive APIs for speculative state management. Inferno is such a functional model construction framework and has significantly improved productivity in modeling a variety of sophisticated data speculation microarchitecture techniques.
207181396
BLoG: Post-Silicon bug localization in processors using bug localization graphs
Post-silicon bug localization — the process of identifying the location of a detected hardware bug and the cycle(s) during which the bug produces error(s) — is a major bottleneck for complex integrated circuits. Instruction Footprint Recording and Analysis (IFRA) is a promising post-silicon bug localization technique for complex processor cores. However, applying IFRA to new processor microarchitectures can be challenging due to the manual effort required to implement special microarchitecture-dependent analysis techniques for bug localization. This paper presents the Bug Localization Graph (BLoG) framework that enables application of IFRA to new processor microarchitectures with reduced manual effort. Results obtained from an industrial microarchitectural simulator modeling a state-of-the-art complex commercial microarchitecture (Intel Nehalem, the foundation for the Intel Core™ i7 and Core™ i5 processor families) demonstrate that BLoG-assisted IFRA enables effective and efficient post-silicon bug localization for complex processors with high bug localization accuracy at low cost.
13981080
Pangaea: A tightly-coupled IA32 heterogeneous chip multiprocessor
Moore's Law and the drive towards performance efficiency have led to the on-chip integration of general-purpose cores with special-purpose accelerators. Pangaea is a heterogeneous CMP design for non-rendering workloads that integrates IA32 CPU cores with non-IA32 GPU-class multi-cores, extending the current state-of-the-art CPU-GPU integration that physically “fuses” existing CPU and GPU designs. Pangaea introduces (1) a resource repartitioning of the GPU, where the hardware budget dedicated for 3D-specific graphics processing is used to build more general-purpose GPU cores, and (2) a 3-instruction extension to the IA32 ISA that supports tighter architectural integration and fine-grain shared memory collaborative multithreading between the IA32 CPU cores and the non-IA32 GPU cores. We implement Pangaea and the current CPU-GPU designs in fully-functional synthesizable RTL based on the production quality RTL of an IA32 CPU and an Intel GMA X4500 GPU. On a 65 nm ASIC process technology, the legacy graphics-specific fixed-function hardware has the area of 9 GPU cores and total power consumption of 5 GPU cores. With the ISA extensions, the latency from the time an IA32 core spawns a GPU thread to the time the thread begins execution is reduced from thousands of cycles to fewer than 30 cycles. Pangaea is synthesized on a FPGA-based prototype and runs off-the-shelf IA32 OSes. A set of general-purpose non-graphics workloads demonstrate speedups of up to 8.8×.
40482370
Quantitative evaluation of the register stack engine and optimizations for future Itanium processors
This paper examines the efficiency of the register stack engine (RSE) in the canonical Itanium architecture, and introduces novel optimization techniques to enhance the RSE performance. To minimize spills and fills of the physical register file, optimizations are applied to reduce internal fragmentation in statically allocated register stack frames. Through the use of dynamic register usage (DRU) and dead register value information (DVI), the processor can dynamically guide allocation and deallocation of register frames. Consequently, a speculatively allocated register frame with a dynamically determined frame size can be much smaller than the statically determined frame size, thus achieving minimum spills and fills. Using the register stack engine (RSE) in the canonical Itanium architecture as the baseline reference, we thoroughly study and gauge the tradeoffs of the RSE and the proposed optimizations using a set of SPEC CPU2000 benchmarks built with different compiler optimizations. A combination of frame allocation policies using the most frequent frame size and deallocation policies using dead register information proves to be highly effective. On average, a 71% reduction in aggregate spills and fills can be achieved over the baseline reference.
62483723
Dynamic speculative precomputation
A large number of memory accesses in memory-bound applications are irregular, such as pointer dereferences, and can be effectively targeted by thread-based prefetching techniques like Speculative Precomputation. These techniques execute instructions, for example on an available SMT thread context, that have been extracted directly from the program they are trying to accelerate. Proposed techniques typically require manual user intervention to extract and optimize instruction sequences. This paper proposes Dynamic Speculative Precomputation, which performs all necessary instruction analysis, extraction, and optimization through the use of back-end instruction analysis hardware, located off the processor's critical path. For a set of memory limited benchmarks an average speedup of 14% is achieved when constructing simple p-slices, and this gain grows to 33% when making use of aggressive optimizations.
14739906
Helper threads via virtual multithreading
Memory latency dominates the performance of many applications on modern processors, despite advances in caches and prefetching techniques. Numerous prefetching techniques, both in hardware and software, try to alleviate the memory bottleneck. One such technique, known as helper threading improves single-thread performance on a simultaneous multithreaded architecture (SMT), which shares processor resources, including caches, among logical threads. It uses otherwise idle hardware thread contexts to execute speculative threads on behalf of the main thread. Helper threading accelerates a program by exploiting a processor's multithreading capability to run assist threads. Based on the helper threading usage model, virtual multithreading (VMT), a form of switch-on-event user-level multithreading, can improve performance for real-world workloads with a wall-clock speedup of 5.0 to 38.5 percent
424163
Reliable Observer-Based Control Against Sensor Failures for Systems With Time Delays in Both State and Input
For systems with both state and input time delays, a novel state and sensor fault observer is proposed in this paper to estimate system states and sensor faults simultaneously. In this design, a descriptor system approach and a linear matrix inequality technique are adopted, where the considered sensor fault may be in any form, even unbounded. Unbounded sensor faults will make the system fail unavoidably; it is indispensable to derive a reliable control scheme against sensor failures. Using the estimated state and sensor fault, a reliable observer-based controller is proposed, which makes the system work well no matter whether sensor faults occur or not. The present approaches are next extended to the case for systems with multiple time delays. Finally, a simulation example of the network of three cascaded reactors is used to illustrate the design procedure and demonstrate the efficiency of the present techniques.
9527664
Vertex-Disjoint Triangles in Claw-Free Graphs with Minimum Degree at Least Three
. Our main result is as follows: For any integer , if G is a claw-free graph of order at least and with minimum degree at least 3, then G contains k vertex-disjoint triangles unless G is of order and G belongs to a known class of graphs. We also construct a claw-free graph with minimum degree 3 on n vertices for each such that it does not contain k vertex-disjoint triangles. We put forward a conjecture on vertex-disjoint triangles in -free graphs.
7096747
A Performance Study of Secure Data Mining on the Cell Processor
This paper examines the potential of the Cell processor as a platform for secure data mining on the future volunteer computing systems. Volunteer computing platforms have the potential to provide massive computing power. However, privacy and security concerns prevent using volunteer computing for data mining of sensitive data. The Cell processor comes with a hardware security feature. The secure volunteer data mining can be achieved by using this hardware security feature. In this paper, we present a general security scheme for the volunteer computing, and a secure parallelized K-Means clustering algorithm for the Cell processor. We also evaluate the performance of the algorithm on the Cell secure system simulator. Evaluation results indicate that the proposed secure data clustering outperforms a non-secure clustering algorithm on the general purpose CPU, but incurs a huge performance overhead introduced by the decryption process of the Cell security features.
9404376
An XML-Based Implementation of Multimodal Affective Annotation
In simple cases, affective computing is a computational device recognizing and acting upon the emotions of its user or having (or simulating having) emotions of its own in complex cases. Multimodal technology is currently one of the hottest focuses in affective computing research. However, the lack of a large-scale multimodal database limits the research to some respective and scattered fields, such as affective recognition by video or by audio. This paper describes the development and implementation of an XML-based multimodal affective annotation system which is called MAAS (Multimodal Affective Annotation System). MAAS contains a hierarchical affective annotation model based on the 3-dimensional affect space derived from Mehrabian’s PAD temperament scale. The final annotation file is formed in XML format in order to interchange the resources with other research groups conveniently.
2015833
A Workflow Management Mechanism for Peer-to-Peer Computing Platforms
This paper proposes a workflow management mechanism to address a neglected aspect of existing P2P computing platforms – the lack of support for various computational models. In the workflow management mechanism, a workflow description file is used to define the workflow diagram of the target application. We develop a prototype system, and evaluate it using a test program to demonstrate how the workflow management mechanism effectively works.