Disparate deployment models of cloud computing pose varying requirements on cloud infrastructure components such as networking, storage, provisioning, and security. Infrastructure providers need to study these and often create custom infrastructure components to satisfy these requirements. A major challenge in the research and development of these cloud infrastructure solutions, however, is the availability of customizable platforms for experimentation and trade-off analysis of the various hardware and software components. Most platforms are either general purpose or bespoke solutions created to assist a particular task, too rigid to allow meaningful customization. In this work, we present a 100G reconfigurable smartNIC prototyping platform called Janus that enables cloud infrastructure research and hardware-software co-design of infrastructure components such as hypervisor, secure boot, software defined networking and distributed storage. The platform provides a path to optimize the stack by offloading the functionalities from the host x86 to the embedded processor on the smartNIC and optimize performance by moving pieces to hardware using P4. Further, our platform provides hardware-enforced isolation of cloud network control plane, thereby securing the control plane from the tenants even for bare-metal deployments.

We demonstrate the use of an FPGA as a memory buffer in a POWER8® system, creating a novel prototyping platform that enables innovation in the memory subsystem of POWER-based servers. Our platform, called ConTutto, is pin-compatible with POWER8 buffered memory DIMMs and plugs into a memory slot of a standard POWER8 processor system, running at aggregate memory channel speeds of 35 GB/s per link. ConTutto, which means "with everything", is a platform to experiment with different memory technologies, such as STT-MRAM and NAND Flash, in an end-to-end system context. Enablement of STT-MRAM and NVDIMM using ConTutto shows up to 12.5x lower latency and 7.5x higher bandwidth compared to the respective technologies when attached to the PCIe bus. Moreover, due to the unique attach-point of the FPGA between the processor and system memory, ConTutto provides a means for in-line acceleration of certain computations on-route to memory, and enables sensitivity analysis for memory latency while running real applications. To the best of our knowledge, ConTutto is the first ever FPGA platform on the memory bus of a server class processor.

Drawing on neuroscience, we have developed a parallel, event-driven kernel for neurosynaptic computation, that is efficient with respect to computation, memory, and communication. Building on the previously demonstrated highly optimized software expression of the kernel, here, we demonstrate True North, a co-designed silicon expression of the kernel. True North achieves five orders of magnitude reduction in energy to-solution and two orders of magnitude speedup in time-to solution, when running computer vision applications and complex recurrent neural network simulations. Breaking path with the von Neumann architecture, True North is a 4,096 core, 1 million neuron, and 256 million synapse brain-inspired neurosynaptic processor, that consumes 65mW of power running at real-time and delivers performance of 46 Giga-Synaptic OPS/Watt. We demonstrate seamless tiling of True North chips into arrays, forming a foundation for cortex-like scalability. True North's unprecedented time-to-solution, energy-to-solution, size, scalability, and performance combined with the underlying flexibility of the kernel enable a broad range of cognitive applications.

Software based tools for simulation are not keeping up with the demands for increased chip and system design complexity. In this paper, we describe a cycle-accurate and cycle-reproducible large-scale FPGA platform that is designed from the ground up to accelerate logic verification of the Bluegene/Q compute node ASIC, a multi-processor SOC implemented in IBM's 45 nm SOI CMOS technology. This paper discusses the challenges for constructing such large-scale FPGA platforms, including design partitioning, clocking & synchronization, and debugging support, as well as our approach for addressing these challenges without sacrificing cycle accuracy and cycle reproducibility. The resulting fullchip simulation of the Bluegene/Q compute node ASIC runs at a simulated processor clock speed of 4 MHz, over 100,000 times faster than the logic level software simulation of the same design. The vast increase in simulation speed provides a new capability in the design cycle that proved to be instrumental in logic verification as well as early software development and performance validation for Bluegene/Q.

FPGAs have become indispensible in processor design, bring-up and debug. Traditionally FPGAs have been used in prototyping, allowing end-users to emulate functionality of a specific component of a processor. However, as the complexity of processors grows, another aspect of processor design, RTL verification, has become a prime target for acceleration using FPGAs. Software-only RTL simulation and verification tools are no longer sufficient for many verification tasks as they often incur long execution time penalties. Software simulation time for a basic Linux kernel bring-up on a BlueGene/Q [1] processor, with 16 user PowerPC A2 cores, for example, could easily exceed several years.

We introduce an importance sampling (IS) method that successfully simulates the performance of Low density Parity Check (LDPC) Codes in an AWGN channel at very low bit error rates (BERs). By effectively finding and biasing bit node combinations that are the dominant sources of error events, called trapping sets, the developed technique provokes more frequent decoder failures. Consequently, fewer simulation runs and higher simulation gains are achieved.

We report a proof-of-concept demonstration of 2- Gbps uncompressed HDTV transmission using a 60-GHz SiGe radio chipset. We took a single-carrier approach with a usual DQPSK modulation scheme, assuming an LOS environment, and implemented the system with FPGAs. At the same time, in order to take care of more frequent sync/burst errors in high-data-rate single-carrier approaches, we equipped the baseband with effi- cient random/packet error recovery and symbol-timing recovery with an effective interpolation method. As a result, a clear and crisp image was obtained in the end-to-end transmission. I. INTRODUCTION

We introduce an Importance Sampling (IS) method that successfully simulates the performance of Low density Parity Check (LDPC) Codes in an AWGN channel at very low bit error rates (BERs). By effectively finding and biasing bit node combinations that are the dominant sources of error events, called trapping sets, the developed technique provokes more frequent decoder failures. Consequently, fewer simulation runs and higher simulation gains are achieved. Regardless of the block size of an LDPC code, only a few dominant trapping set classes cause decoder failures at low BER regions. Therefore, the proposed technique allows the performance evaluation for any size LDPC code at very low BER regions with remarkable simulation gains. For BERs of 10-20, we observed simulation gains on the order of 1014.