This work presents a framework which detects online and at operand level of granularity all the vectors which excite a set of diagnosed failures in combinational modules. The failures may be of various types and may change over time. We propose to utilize this ability to detect failures at operand level of granularity to improve yield, by not discarding those chips containing failing and redundant computational units as long as they are not failing at the same time. The main challenge in realization of such a framework is the ability for on-chip storage of all the (test) vectors which excite the set of diagnosed failures. A major contribution of this work is to significantly minimize the number of stored test cubes by inserting only a few but carefully-selected "false alarm" vectors. As a result, a computational unit may be mis-diagnosed as failing for a given operand however we show such cases are rare and the chip may continue to be used.

Dynamic voltage and frequency scaling can provide substantial energy savings but is limited by SRAM since some cells will fail at very low voltages. Due to process variation effects, a small subset of SRAM cells will be more sensitive to voltage reduction, requiring increased margins and limiting energy savings. Since large arrays like caches are most vulnerable to cell failures, recent proposals suggest disabling failing portions of the cache to enable low voltage operation. Although such approaches save power, energy reduction is limited because reducing the effective cache size increases program runtimes. In this paper, we present iPatch, a solution to regain this lost performance and enable energy savings by exploiting the redundancy inherent in superscalar processors. By relying on existing microarchitectural structures and mechanisms to "patch" the faulty parts of caches, we enable further energy reduction with minimal overhead and complexity. Furthermore, because no critical paths or circuits are affected by our implementation, there is no impact on normal-voltage operation. For high cell failure rates, our results show significant energy savings with iPatch as well as an 18% reduction in energy-delay product compared to prior work.

Protecting main memories from soft errors typically requires special dual-inline memory modules (DIMMs) which incorporate at least one extra chip per rank to store error-correcting codes (ECC). This increases the cost of the DIMM as well as its power consumption. To avoid these costs, some proposals have suggested protecting non-ECC DIMMs by allocating a portion of memory space to store ECC metadata. However, such proposals can significantly shrink the available memory space while degrading performance due to extra memory accesses. In this work, we propose a technique called COP which uses block-level compression to make room for ECC check bits in DRAM. Because a compressed block with check bits is the same size as an uncompressed block, no extra memory accesses are required and the memory space is not reduced. Unlike other approaches that require explicit compression-tracking metadata, COP employs a novel mechanism that relies on ECC to detect compressed data. Our results show that COP can reduce the DRAM soft error rate by 93% with no storage overhead and negligible impact on performance. We also propose a technique using COP to protect both compressible and incompressible data with minimal storage and performance overheads.

With the advent of general-purpose GPU computing, it is becoming increasingly desirable to protect GPUs from soft errors. For high computation throughout, GPUs must store a significant amount of state and have many execution units. The high power and area costs of full protection from soft errors make selective protection techniques attractive. Such approaches provide maximum error coverage within a fixed area or power limit, but typically treat all errors equally. We observe that for many floating-point-intensive GPGPU applications, small magnitude errors may have little effect on results, while large magnitude errors can be amplified to have a significant negative impact. We therefore propose a novel precision-aware protection approach for the GPU execution logic and register file to mitigate large magnitude errors. We also propose an architecture modification to optimize error coverage for integer computations. Our approach combines selective logic hardening, targeted checker circuits, and intelligent register file encoding for best error protection. We demonstrate that our approach can reduce the mean error magnitude by up to 87% compared to a traditional selective protection approach with the same overhead.

Delay variation due to dopant fluctuation is expected to become more prominent in future technology generations. To regain performance lost due to within-die variations, many architectural techniques propose modified timing schemes such as time borrowing or variable latency execution. As an alternative that specifically targets random variation, we propose introducing redundancy along the processor datapath in the form of one or more extra bitslices. This approach allows us to leave dummy slices in the datapath unused to avoid excessively slow critical paths created by delay variations. We examine the benefits of applying this technique to potential critical paths such as the ALU and register file, and demonstrate that our technique can significantly reduce the delay penalty due to variation. By adding a single bitslice, for instance, we can reduce this delay penalty by 10%. Finally, we discuss heuristics for configuring our redundant design after fabrication.

With shrinking transistor sizes and supply voltages, errors in combinational logic due to radiation particle strikes are on the rise. A broad range of applications will soon require protection from this type of error, requiring an effective and inexpensive solution. Many previously proposed logic protection techniques rely on duplicate logic or latches, incurring high overheads. In this paper, we present a technique for transient error detection using parity trees for power and area efficiency. This approach is highly customizable, allowing adjustment of a number of parameters for optimal error coverage and overhead. We present simulation results comparing our scheme to latch duplication, showing on average greater than 55% savings in area and power overhead for the same error coverage. We also demonstrate adding protection to reach a target logic soft error rate, constituting at best a 59X reduction in the error rate with under 2% power and area overhead.

Modern out-of-order processors require a large number of register file access ports. However, adding more ports can drastically increase the delay, power and area of the register file. This relationship imposes constraints on existing superscalar designs while impeding implementation of faster and wider out-of-order processors. In this paper, we present a novel multi-ported register file using concepts from network coding. We split a true multi-ported register file into two interleaved banks, each having half the read and write ports. A third bank, storing the XOR of the write backs to the other two banks, is added to amplify the read and write bandwidth. When compared to a conventional register file, our 8R4W 128-entry coded CRAM register file reduces leakage power by 48%, area by 29% and delay by 9%. In addition, for SPEC2006 benchmarks, our implementation consumes 40% less register file dynamic energy on average with IPC degradation of 3%.